Face Generation

In this project, you'll use generative adversarial networks to generate new images of faces.

Get the Data

You'll be using two datasets in this project:

  • MNIST
  • CelebA

Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.

If you're using FloydHub, set data_dir to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".

In [1]:
data_dir = './data'

# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'


"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper

helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
Found mnist Data
Found celeba Data

Explore the Data

MNIST

As you're aware, the MNIST dataset contains images of handwritten digits. You can view the first number of examples by changing show_n_images.

In [2]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot

mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
Out[2]:
<matplotlib.image.AxesImage at 0x7f50162862b0>

CelebA

The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images.

In [3]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Out[3]:
<matplotlib.image.AxesImage at 0x7f50161aee48>

Preprocess the Data

Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

The MNIST images are black and white images with a single color channel while the CelebA images have 3 color channels (RGB color channel).

Build the Neural Network

You'll build the components necessary to build a GANs by implementing the following functions below:

  • model_inputs
  • discriminator
  • generator
  • model_loss
  • model_opt
  • train

Check the Version of TensorFlow and Access to GPU

This will check to make sure you have the correct version of TensorFlow and access to a GPU

In [4]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf

# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer.  You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))

# Check for a GPU
if not tf.test.gpu_device_name():
    warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
    print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
TensorFlow Version: 1.2.1
Default GPU Device: /gpu:0

Input

Implement the model_inputs function to create TF Placeholders for the Neural Network. It should create the following placeholders:

  • Real input images placeholder with rank 4 using image_width, image_height, and image_channels.
  • Z input placeholder with rank 2 using z_dim.
  • Learning rate placeholder with rank 0.

Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)

In [5]:
import problem_unittests as tests

def model_inputs(image_width, image_height, image_channels, z_dim):
    """
    Create the model inputs
    :param image_width: The input image width
    :param image_height: The input image height
    :param image_channels: The number of image channels
    :param z_dim: The dimension of Z
    :return: Tuple of (tensor of real input images, tensor of z data, learning rate)
    """
    real_input_image = tf.placeholder(
        tf.float32, [None, image_width, image_height, image_channels])
    z_input_image = tf.placeholder(tf.float32, [None, z_dim])
    learning_rate = tf.placeholder(tf.float32)    
    return real_input_image, z_input_image, learning_rate


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
ERROR:tensorflow:==================================
Object was never used (type <class 'tensorflow.python.framework.ops.Operation'>):
<tf.Operation 'assert_rank_2/Assert/Assert' type=Assert>
If you want to mark it as used call its "mark_used()" method.
It was originally created here:
['File "/home/carnd/anaconda3/envs/dl/lib/python3.5/runpy.py", line 184, in _run_module_as_main\n    "__main__", mod_spec)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/runpy.py", line 85, in _run_code\n    exec(code, run_globals)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/__main__.py", line 3, in <module>\n    app.launch_new_instance()', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/traitlets/config/application.py", line 658, in launch_instance\n    app.start()', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/kernelapp.py", line 474, in start\n    ioloop.IOLoop.instance().start()', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/zmq/eventloop/ioloop.py", line 177, in start\n    super(ZMQIOLoop, self).start()', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tornado/ioloop.py", line 887, in start\n    handler_func(fd_obj, events)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tornado/stack_context.py", line 275, in null_wrapper\n    return fn(*args, **kwargs)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events\n    self._handle_recv()', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv\n    self._run_callback(callback, msg)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback\n    callback(*args, **kwargs)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tornado/stack_context.py", line 275, in null_wrapper\n    return fn(*args, **kwargs)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher\n    return self.dispatch_shell(stream, msg)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell\n    handler(stream, idents, msg)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 390, in execute_request\n    user_expressions, allow_stdin)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/ipkernel.py", line 196, in do_execute\n    res = shell.run_cell(code, store_history=store_history, silent=silent)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/zmqshell.py", line 501, in run_cell\n    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell\n    interactivity=interactivity, compiler=compiler, result=result)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2827, in run_ast_nodes\n    if self.run_code(code, result):', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code\n    exec(code_obj, self.user_global_ns, self.user_ns)', 'File "<ipython-input-5-38424e90053c>", line 22, in <module>\n    tests.test_model_inputs(model_inputs)', 'File "/home/carnd/deep-learning/face_generation/problem_unittests.py", line 12, in func_wrapper\n    result = func(*args)', 'File "/home/carnd/deep-learning/face_generation/problem_unittests.py", line 68, in test_model_inputs\n    _check_input(learn_rate, [], \'Learning Rate\')', 'File "/home/carnd/deep-learning/face_generation/problem_unittests.py", line 34, in _check_input\n    _assert_tensor_shape(tensor, shape, \'Real Input\')', 'File "/home/carnd/deep-learning/face_generation/problem_unittests.py", line 20, in _assert_tensor_shape\n    assert tf.assert_rank(tensor, len(shape), message=\'{} has wrong rank\'.format(display_name))', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tensorflow/python/ops/check_ops.py", line 617, in assert_rank\n    dynamic_condition, data, summarize)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tensorflow/python/ops/check_ops.py", line 571, in _assert_rank_condition\n    return control_flow_ops.Assert(condition, data, summarize=summarize)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py", line 170, in wrapped\n    return _add_should_use_warning(fn(*args, **kwargs))', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py", line 139, in _add_should_use_warning\n    wrapped = TFShouldUseWarningWrapper(x)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py", line 96, in __init__\n    stack = [s.strip() for s in traceback.format_stack()]']
==================================
Tests Passed

Discriminator

Implement discriminator to create a discriminator neural network that discriminates on images. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the discriminator, tensor logits of the discriminator).

In [7]:
def discriminator(images, reuse=False, alpha=0.2):
    """
    Create the discriminator network
    :param images: Tensor of input image(s)
    :param reuse: Boolean if the weights should be reused
    :return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
    """
    def conv2d(x, filters):
        return tf.layers.conv2d(x, filters, kernel_size=5, strides=2, padding='same')
    
    def leakyLeRU(x):
        return tf.maximum(alpha * x, x)        

    with tf.variable_scope('discriminator', reuse=reuse):    
        x = conv2d(images, 64)
        x = leakyLeRU(x)
        
        x = conv2d(images, 128)
        x = tf.layers.batch_normalization(x, training=True)
        x = leakyLeRU(x)
        
        x = conv2d(images, 256)
        x = tf.layers.batch_normalization(x, training=True)
        x = leakyLeRU(x)

        x = conv2d(images, 512)
        x = tf.layers.batch_normalization(x, training=True)
        x = leakyLeRU(x)

        flat = tf.reshape(x, (-1, 4*4*512))
        logits = tf.layers.dense(flat, 1)
        out = tf.sigmoid(logits)
            
    return logits, out


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Tests Passed

Generator

Implement generator to generate an image using z. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim images.

In [8]:
def generator(z, out_channel_dim, is_train=True, alpha=0.2):
    """
    Create the generator network
    :param z: Input z
    :param out_channel_dim: The number of channels in the output image
    :param is_train: Boolean if generator is being used for training
    :return: The tensor output of the generator
    """
    def conv2d_transpose(x, filters):
        return tf.layers.conv2d_transpose(x, filters, kernel_size=5, strides=2, padding='same')
        
    def leakyLeRU(x):
        return tf.maximum(alpha * x, x)      
    
    reuse = not is_train
    with tf.variable_scope('generator', reuse=reuse):
        x = tf.layers.dense(z, 7 * 7 * 512)
        x = tf.reshape(x, (-1, 7, 7, 512))
        x = tf.layers.batch_normalization(x, training=is_train)
        x = leakyLeRU(x)
        # 14x14x512
                
        x = conv2d_transpose(x, 256)
        x = tf.layers.batch_normalization(x, training=is_train)
        x = leakyLeRU(x)
        # 28x28x256
        
        logits = conv2d_transpose(x, out_channel_dim)
        # 28x28x3        
        out = tf.tanh(logits)
                
    return out


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Tests Passed

Loss

Implement model_loss to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:

  • discriminator(images, reuse=False)
  • generator(z, out_channel_dim, is_train=True)
In [9]:
def model_loss(input_real, input_z, out_channel_dim, alpha=0.2):
    """
    Get the loss for the discriminator and generator
    :param input_real: Images from the real dataset
    :param input_z: Z input
    :param out_channel_dim: The number of channels in the output image
    :return: A tuple of (discriminator loss, generator loss)
    """
    g_model = generator(input_z, out_channel_dim, alpha=alpha)
    d_model_real, d_logits_real = discriminator(input_real, reuse=False, alpha=alpha)
    d_model_fake, d_logits_fake = discriminator(g_model, reuse=True, alpha=alpha)
    
    # Discriminator real loss. Labels are 1 since the discriminator attempts to detect
    # real images.
    d_loss_real = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(
            logits=d_logits_real, labels=tf.ones_like(d_model_real)))
    
    # Discriminator fake loss. Labels are 0 since the discriminator attempts to detect
    # fake images.
    d_loss_fake = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(
            logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
    
    d_loss = d_loss_real + d_loss_fake
    
    # Generator loss. Labels are 0 since the generator attempts to fake
    # the discriminator.
    g_loss = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(
            logits=d_logits_fake, labels=tf.ones_like(d_model_fake)))

    return d_loss, g_loss    


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Tests Passed

Optimization

Implement model_opt to create the optimization operations for the GANs. Use tf.trainable_variables to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).

In [10]:
def model_opt(d_loss, g_loss, learning_rate, beta1):
    """
    Get optimization operations
    :param d_loss: Discriminator loss Tensor
    :param g_loss: Generator loss Tensor
    :param learning_rate: Learning Rate Placeholder
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :return: A tuple of (discriminator training operation, generator training operation)
    """
    t_vars = tf.trainable_variables()
    d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
    g_vars = [var for var in t_vars if var.name.startswith('generator')]

    with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
        d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(
            d_loss, var_list=d_vars)
        g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(
            g_loss, var_list=g_vars)

    return d_train_opt, g_train_opt    


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
Tests Passed

Neural Network Training

Show Output

Use this function to show the current output of the generator during training. It will help you determine how well the GANs is training.

In [11]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np

def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
    """
    Show example output for the generator
    :param sess: TensorFlow session
    :param n_images: Number of Images to display
    :param input_z: Input Z Tensor
    :param out_channel_dim: The number of channels in the output image
    :param image_mode: The mode to use for images ("RGB" or "L")
    """
    cmap = None if image_mode == 'RGB' else 'gray'
    z_dim = input_z.get_shape().as_list()[-1]
    example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])

    samples = sess.run(
        generator(input_z, out_channel_dim, False),
        feed_dict={input_z: example_z})

    images_grid = helper.images_square_grid(samples, image_mode)
    pyplot.imshow(images_grid, cmap=cmap)
    pyplot.show()

Train

Implement train to build and train the GANs. Use the following functions you implemented:

  • model_inputs(image_width, image_height, image_channels, z_dim)
  • model_loss(input_real, input_z, out_channel_dim)
  • model_opt(d_loss, g_loss, learning_rate, beta1)

Use the show_generator_output to show generator output while you train. Running show_generator_output for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator output every 100 batches.

In [12]:
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
    """
    Train the GAN
    :param epoch_count: Number of epochs
    :param batch_size: Batch Size
    :param z_dim: Z dimension
    :param learning_rate: Learning Rate
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :param get_batches: Function to get batches
    :param data_shape: Shape of the data
    :param data_image_mode: The image mode to use for images ("RGB" or "L")
    """
    image_width = data_shape[1]
    image_height = data_shape[2]
    image_channels = data_shape[3]    
    real_input_image, z_input_image, learning_rate_pf = model_inputs(
        image_width, image_height, image_channels, z_dim)
            
    d_loss, g_loss = model_loss(real_input_image, z_input_image, image_channels, alpha=0.2)
    d_opt, g_opt = model_opt(d_loss, g_loss, learning_rate_pf, beta1)    
    
    samples, losses = [], []
    steps = 0
    print_every = 10
    show_every = 50
    
    with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())
        for epoch_i in range(epoch_count):
            for batch_images in get_batches(batch_size):
                steps += 1

                # Sample random noise for G
                batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
                            
                # Run optimizers
                _ = sess.run(d_opt, feed_dict={
                        real_input_image: batch_images,
                        z_input_image: batch_z,
                        learning_rate_pf: learning_rate})
                _ = sess.run(g_opt, feed_dict={
                        real_input_image: batch_images, 
                        z_input_image: batch_z,
                        learning_rate_pf: learning_rate})

                if steps % print_every == 0:
                    # At the end of each epoch, get the losses and print them out
                    train_loss_d = d_loss.eval({real_input_image: batch_images, z_input_image: batch_z})
                    train_loss_g = g_loss.eval({real_input_image: batch_images, z_input_image: batch_z})

                    print("Epoch {}/{}...".format(epoch_i + 1, epoch_count),
                          "Discriminator Loss: {:.4f}...".format(train_loss_d),
                          "Generator Loss: {:.4f}".format(train_loss_g))
                    losses.append((train_loss_d, train_loss_g))

                if steps % show_every == 0:    
                    show_generator_output(sess, 64, z_input_image, image_channels, data_image_mode)

MNIST

Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.

In [92]:
batch_size = 32
z_dim = 64
learning_rate = 0.0004
beta1 = 0.5


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2

mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
          mnist_dataset.shape, mnist_dataset.image_mode)
Epoch 1/2... Discriminator Loss: 1.0979... Generator Loss: 0.6873
Epoch 1/2... Discriminator Loss: 1.0568... Generator Loss: 0.6704
Epoch 1/2... Discriminator Loss: 1.4653... Generator Loss: 0.4338
Epoch 1/2... Discriminator Loss: 1.1574... Generator Loss: 0.6295
Epoch 1/2... Discriminator Loss: 1.0492... Generator Loss: 0.6878
Epoch 1/2... Discriminator Loss: 1.1062... Generator Loss: 0.6601
Epoch 1/2... Discriminator Loss: 1.2381... Generator Loss: 0.5686
Epoch 1/2... Discriminator Loss: 1.1635... Generator Loss: 0.6248
Epoch 1/2... Discriminator Loss: 1.4263... Generator Loss: 0.4990
Epoch 1/2... Discriminator Loss: 1.4770... Generator Loss: 0.5271
Epoch 1/2... Discriminator Loss: 1.4497... Generator Loss: 0.4737
Epoch 1/2... Discriminator Loss: 1.4340... Generator Loss: 0.5228
Epoch 1/2... Discriminator Loss: 1.4059... Generator Loss: 0.5628
Epoch 1/2... Discriminator Loss: 1.4006... Generator Loss: 0.5846
Epoch 1/2... Discriminator Loss: 1.3799... Generator Loss: 0.5934
Epoch 1/2... Discriminator Loss: 1.4089... Generator Loss: 0.5671
Epoch 1/2... Discriminator Loss: 1.3585... Generator Loss: 0.6075
Epoch 1/2... Discriminator Loss: 1.3423... Generator Loss: 0.5904
Epoch 1/2... Discriminator Loss: 1.3179... Generator Loss: 0.6416
Epoch 1/2... Discriminator Loss: 1.3482... Generator Loss: 0.6203
Epoch 1/2... Discriminator Loss: 1.3020... Generator Loss: 0.6130
Epoch 1/2... Discriminator Loss: 1.3420... Generator Loss: 0.6259
Epoch 1/2... Discriminator Loss: 1.3309... Generator Loss: 0.6260
Epoch 1/2... Discriminator Loss: 1.3579... Generator Loss: 0.5852
Epoch 1/2... Discriminator Loss: 1.2761... Generator Loss: 0.6360
Epoch 1/2... Discriminator Loss: 1.3290... Generator Loss: 0.5845
Epoch 1/2... Discriminator Loss: 1.3073... Generator Loss: 0.6097
Epoch 1/2... Discriminator Loss: 1.3432... Generator Loss: 0.6057
Epoch 1/2... Discriminator Loss: 1.3251... Generator Loss: 0.5900
Epoch 1/2... Discriminator Loss: 1.2592... Generator Loss: 0.6538
Epoch 1/2... Discriminator Loss: 1.2811... Generator Loss: 0.6395
Epoch 1/2... Discriminator Loss: 1.2939... Generator Loss: 0.6405
Epoch 1/2... Discriminator Loss: 1.3319... Generator Loss: 0.5993
Epoch 1/2... Discriminator Loss: 1.3099... Generator Loss: 0.6105
Epoch 1/2... Discriminator Loss: 1.2988... Generator Loss: 0.6350
Epoch 1/2... Discriminator Loss: 1.3342... Generator Loss: 0.5966
Epoch 1/2... Discriminator Loss: 1.3277... Generator Loss: 0.6269
Epoch 1/2... Discriminator Loss: 1.3409... Generator Loss: 0.6063
Epoch 1/2... Discriminator Loss: 1.3423... Generator Loss: 0.5776
Epoch 1/2... Discriminator Loss: 1.3630... Generator Loss: 0.5908
Epoch 1/2... Discriminator Loss: 1.3285... Generator Loss: 0.6216
Epoch 1/2... Discriminator Loss: 1.3194... Generator Loss: 0.6337
Epoch 1/2... Discriminator Loss: 1.3665... Generator Loss: 0.5858
Epoch 1/2... Discriminator Loss: 1.3586... Generator Loss: 0.6061
Epoch 1/2... Discriminator Loss: 1.3631... Generator Loss: 0.5989
Epoch 1/2... Discriminator Loss: 1.3530... Generator Loss: 0.6118
Epoch 1/2... Discriminator Loss: 1.3700... Generator Loss: 0.6006
Epoch 1/2... Discriminator Loss: 1.3320... Generator Loss: 0.6274
Epoch 1/2... Discriminator Loss: 1.3424... Generator Loss: 0.6204
Epoch 1/2... Discriminator Loss: 1.3547... Generator Loss: 0.6076
Epoch 1/2... Discriminator Loss: 1.3201... Generator Loss: 0.6273
Epoch 1/2... Discriminator Loss: 1.3539... Generator Loss: 0.6383
Epoch 1/2... Discriminator Loss: 1.3632... Generator Loss: 0.6162
Epoch 1/2... Discriminator Loss: 1.3609... Generator Loss: 0.5940
Epoch 1/2... Discriminator Loss: 1.3616... Generator Loss: 0.6252
Epoch 1/2... Discriminator Loss: 1.3755... Generator Loss: 0.6113
Epoch 1/2... Discriminator Loss: 1.3588... Generator Loss: 0.6337
Epoch 1/2... Discriminator Loss: 1.3606... Generator Loss: 0.6223
Epoch 1/2... Discriminator Loss: 1.3772... Generator Loss: 0.6242
Epoch 1/2... Discriminator Loss: 1.3381... Generator Loss: 0.6355
Epoch 1/2... Discriminator Loss: 1.3615... Generator Loss: 0.6290
Epoch 1/2... Discriminator Loss: 1.3761... Generator Loss: 0.6273
Epoch 1/2... Discriminator Loss: 1.3654... Generator Loss: 0.6258
Epoch 1/2... Discriminator Loss: 1.3691... Generator Loss: 0.6234
Epoch 1/2... Discriminator Loss: 1.3693... Generator Loss: 0.6328
Epoch 1/2... Discriminator Loss: 1.3709... Generator Loss: 0.6208
Epoch 1/2... Discriminator Loss: 1.3613... Generator Loss: 0.6192
Epoch 1/2... Discriminator Loss: 1.3547... Generator Loss: 0.6337
Epoch 1/2... Discriminator Loss: 1.3690... Generator Loss: 0.6258
Epoch 1/2... Discriminator Loss: 1.3573... Generator Loss: 0.6271
Epoch 1/2... Discriminator Loss: 1.3726... Generator Loss: 0.6241
Epoch 1/2... Discriminator Loss: 1.3681... Generator Loss: 0.6275
Epoch 1/2... Discriminator Loss: 1.3708... Generator Loss: 0.6195
Epoch 1/2... Discriminator Loss: 1.3755... Generator Loss: 0.6407
Epoch 1/2... Discriminator Loss: 1.3694... Generator Loss: 0.6371
Epoch 1/2... Discriminator Loss: 1.3671... Generator Loss: 0.6382
Epoch 1/2... Discriminator Loss: 1.3665... Generator Loss: 0.6290
Epoch 1/2... Discriminator Loss: 1.3759... Generator Loss: 0.6325
Epoch 1/2... Discriminator Loss: 1.3665... Generator Loss: 0.6269
Epoch 1/2... Discriminator Loss: 1.3719... Generator Loss: 0.6389
Epoch 1/2... Discriminator Loss: 1.3639... Generator Loss: 0.6361
Epoch 1/2... Discriminator Loss: 1.3590... Generator Loss: 0.6318
Epoch 1/2... Discriminator Loss: 1.3660... Generator Loss: 0.6391
Epoch 1/2... Discriminator Loss: 1.3630... Generator Loss: 0.6448
Epoch 1/2... Discriminator Loss: 1.3752... Generator Loss: 0.6338
Epoch 1/2... Discriminator Loss: 1.3737... Generator Loss: 0.6404
Epoch 1/2... Discriminator Loss: 1.3726... Generator Loss: 0.6388
Epoch 1/2... Discriminator Loss: 1.3757... Generator Loss: 0.6408
Epoch 1/2... Discriminator Loss: 1.3732... Generator Loss: 0.6360
Epoch 1/2... Discriminator Loss: 1.3683... Generator Loss: 0.6304
Epoch 1/2... Discriminator Loss: 1.3761... Generator Loss: 0.6332
Epoch 1/2... Discriminator Loss: 1.3776... Generator Loss: 0.6426
Epoch 1/2... Discriminator Loss: 1.3646... Generator Loss: 0.6417
Epoch 1/2... Discriminator Loss: 1.3752... Generator Loss: 0.6325
Epoch 1/2... Discriminator Loss: 1.3740... Generator Loss: 0.6395
Epoch 1/2... Discriminator Loss: 1.3691... Generator Loss: 0.6409
Epoch 1/2... Discriminator Loss: 1.3718... Generator Loss: 0.6408
Epoch 1/2... Discriminator Loss: 1.3634... Generator Loss: 0.6273
Epoch 1/2... Discriminator Loss: 1.3729... Generator Loss: 0.6484
Epoch 1/2... Discriminator Loss: 1.3639... Generator Loss: 0.6307
Epoch 1/2... Discriminator Loss: 1.3612... Generator Loss: 0.6396
Epoch 1/2... Discriminator Loss: 1.3597... Generator Loss: 0.6389
Epoch 1/2... Discriminator Loss: 1.3765... Generator Loss: 0.6526
Epoch 1/2... Discriminator Loss: 1.3766... Generator Loss: 0.6458
Epoch 1/2... Discriminator Loss: 1.3675... Generator Loss: 0.6563
Epoch 1/2... Discriminator Loss: 1.3684... Generator Loss: 0.6430
Epoch 1/2... Discriminator Loss: 1.3753... Generator Loss: 0.6495
Epoch 1/2... Discriminator Loss: 1.3687... Generator Loss: 0.6367
Epoch 1/2... Discriminator Loss: 1.3735... Generator Loss: 0.6447
Epoch 1/2... Discriminator Loss: 1.3700... Generator Loss: 0.6414
Epoch 1/2... Discriminator Loss: 1.3710... Generator Loss: 0.6320
Epoch 1/2... Discriminator Loss: 1.3598... Generator Loss: 0.6297
Epoch 1/2... Discriminator Loss: 1.3611... Generator Loss: 0.6507
Epoch 1/2... Discriminator Loss: 1.3678... Generator Loss: 0.6469
Epoch 1/2... Discriminator Loss: 1.3688... Generator Loss: 0.6401
Epoch 1/2... Discriminator Loss: 1.3757... Generator Loss: 0.6458
Epoch 1/2... Discriminator Loss: 1.3691... Generator Loss: 0.6311
Epoch 1/2... Discriminator Loss: 1.3745... Generator Loss: 0.6407
Epoch 1/2... Discriminator Loss: 1.3710... Generator Loss: 0.6448
Epoch 1/2... Discriminator Loss: 1.3672... Generator Loss: 0.6497
Epoch 1/2... Discriminator Loss: 1.3735... Generator Loss: 0.6540
Epoch 1/2... Discriminator Loss: 1.3786... Generator Loss: 0.6529
Epoch 1/2... Discriminator Loss: 1.3679... Generator Loss: 0.6459
Epoch 1/2... Discriminator Loss: 1.3766... Generator Loss: 0.6422
Epoch 1/2... Discriminator Loss: 1.3651... Generator Loss: 0.6386
Epoch 1/2... Discriminator Loss: 1.3762... Generator Loss: 0.6560
Epoch 1/2... Discriminator Loss: 1.3708... Generator Loss: 0.6451
Epoch 1/2... Discriminator Loss: 1.3706... Generator Loss: 0.6508
Epoch 1/2... Discriminator Loss: 1.3655... Generator Loss: 0.6442
Epoch 1/2... Discriminator Loss: 1.3712... Generator Loss: 0.6519
Epoch 1/2... Discriminator Loss: 1.3766... Generator Loss: 0.6365
Epoch 1/2... Discriminator Loss: 1.3655... Generator Loss: 0.6445
Epoch 1/2... Discriminator Loss: 1.3740... Generator Loss: 0.6407
Epoch 1/2... Discriminator Loss: 1.3716... Generator Loss: 0.6400
Epoch 1/2... Discriminator Loss: 1.3656... Generator Loss: 0.6479
Epoch 1/2... Discriminator Loss: 1.3772... Generator Loss: 0.6435
Epoch 1/2... Discriminator Loss: 1.3746... Generator Loss: 0.6480
Epoch 1/2... Discriminator Loss: 1.3736... Generator Loss: 0.6511
Epoch 1/2... Discriminator Loss: 1.3763... Generator Loss: 0.6345
Epoch 1/2... Discriminator Loss: 1.3636... Generator Loss: 0.6446
Epoch 1/2... Discriminator Loss: 1.3758... Generator Loss: 0.6567
Epoch 1/2... Discriminator Loss: 1.3694... Generator Loss: 0.6485
Epoch 1/2... Discriminator Loss: 1.3702... Generator Loss: 0.6492
Epoch 1/2... Discriminator Loss: 1.3781... Generator Loss: 0.6544
Epoch 1/2... Discriminator Loss: 1.3777... Generator Loss: 0.6589
Epoch 1/2... Discriminator Loss: 1.3709... Generator Loss: 0.6391
Epoch 1/2... Discriminator Loss: 1.3715... Generator Loss: 0.6524
Epoch 1/2... Discriminator Loss: 1.3726... Generator Loss: 0.6491
Epoch 1/2... Discriminator Loss: 1.3716... Generator Loss: 0.6431
Epoch 1/2... Discriminator Loss: 1.3702... Generator Loss: 0.6447
Epoch 1/2... Discriminator Loss: 1.3724... Generator Loss: 0.6373
Epoch 1/2... Discriminator Loss: 1.3727... Generator Loss: 0.6481
Epoch 1/2... Discriminator Loss: 1.3759... Generator Loss: 0.6417
Epoch 1/2... Discriminator Loss: 1.3719... Generator Loss: 0.6368
Epoch 1/2... Discriminator Loss: 1.3712... Generator Loss: 0.6432
Epoch 1/2... Discriminator Loss: 1.3715... Generator Loss: 0.6356
Epoch 1/2... Discriminator Loss: 1.3797... Generator Loss: 0.6361
Epoch 1/2... Discriminator Loss: 1.3761... Generator Loss: 0.6419
Epoch 1/2... Discriminator Loss: 1.3748... Generator Loss: 0.6362
Epoch 1/2... Discriminator Loss: 1.3707... Generator Loss: 0.6293
Epoch 1/2... Discriminator Loss: 1.3683... Generator Loss: 0.6406
Epoch 1/2... Discriminator Loss: 1.3582... Generator Loss: 0.6313
Epoch 1/2... Discriminator Loss: 1.3713... Generator Loss: 0.6464
Epoch 1/2... Discriminator Loss: 1.3743... Generator Loss: 0.6539
Epoch 1/2... Discriminator Loss: 1.3729... Generator Loss: 0.6516
Epoch 1/2... Discriminator Loss: 1.3730... Generator Loss: 0.6432
Epoch 1/2... Discriminator Loss: 1.3659... Generator Loss: 0.6435
Epoch 1/2... Discriminator Loss: 1.3791... Generator Loss: 0.6571
Epoch 1/2... Discriminator Loss: 1.3759... Generator Loss: 0.6124
Epoch 1/2... Discriminator Loss: 1.3716... Generator Loss: 0.6456
Epoch 1/2... Discriminator Loss: 1.3678... Generator Loss: 0.6495
Epoch 1/2... Discriminator Loss: 1.3736... Generator Loss: 0.6513
Epoch 1/2... Discriminator Loss: 1.3661... Generator Loss: 0.6422
Epoch 1/2... Discriminator Loss: 1.3732... Generator Loss: 0.6499
Epoch 1/2... Discriminator Loss: 1.3752... Generator Loss: 0.6529
Epoch 1/2... Discriminator Loss: 1.3674... Generator Loss: 0.6293
Epoch 1/2... Discriminator Loss: 1.3731... Generator Loss: 0.6596
Epoch 1/2... Discriminator Loss: 1.3698... Generator Loss: 0.6506
Epoch 1/2... Discriminator Loss: 1.3731... Generator Loss: 0.6469
Epoch 1/2... Discriminator Loss: 1.3745... Generator Loss: 0.6434
Epoch 1/2... Discriminator Loss: 1.3577... Generator Loss: 0.6194
Epoch 1/2... Discriminator Loss: 1.3760... Generator Loss: 0.6500
Epoch 1/2... Discriminator Loss: 1.3807... Generator Loss: 0.6450
Epoch 1/2... Discriminator Loss: 1.3526... Generator Loss: 0.6487
Epoch 1/2... Discriminator Loss: 1.3752... Generator Loss: 0.6280
Epoch 1/2... Discriminator Loss: 1.3770... Generator Loss: 0.6494
Epoch 1/2... Discriminator Loss: 1.3795... Generator Loss: 0.6593
Epoch 2/2... Discriminator Loss: 1.3667... Generator Loss: 0.6500
Epoch 2/2... Discriminator Loss: 1.3712... Generator Loss: 0.6544
Epoch 2/2... Discriminator Loss: 1.3541... Generator Loss: 0.6102
Epoch 2/2... Discriminator Loss: 1.3629... Generator Loss: 0.6493
Epoch 2/2... Discriminator Loss: 1.3738... Generator Loss: 0.6494
Epoch 2/2... Discriminator Loss: 1.3757... Generator Loss: 0.6507
Epoch 2/2... Discriminator Loss: 1.3702... Generator Loss: 0.6428
Epoch 2/2... Discriminator Loss: 1.3771... Generator Loss: 0.6485
Epoch 2/2... Discriminator Loss: 1.3743... Generator Loss: 0.6472
Epoch 2/2... Discriminator Loss: 1.3704... Generator Loss: 0.6451
Epoch 2/2... Discriminator Loss: 1.3718... Generator Loss: 0.6436
Epoch 2/2... Discriminator Loss: 1.3686... Generator Loss: 0.6531
Epoch 2/2... Discriminator Loss: 1.3629... Generator Loss: 0.6262
Epoch 2/2... Discriminator Loss: 1.3651... Generator Loss: 0.6477
Epoch 2/2... Discriminator Loss: 1.3628... Generator Loss: 0.6402
Epoch 2/2... Discriminator Loss: 1.3690... Generator Loss: 0.6486
Epoch 2/2... Discriminator Loss: 1.3733... Generator Loss: 0.6504
Epoch 2/2... Discriminator Loss: 1.3817... Generator Loss: 0.6365
Epoch 2/2... Discriminator Loss: 1.3841... Generator Loss: 0.6413
Epoch 2/2... Discriminator Loss: 1.3772... Generator Loss: 0.6573
Epoch 2/2... Discriminator Loss: 1.3737... Generator Loss: 0.6576
Epoch 2/2... Discriminator Loss: 1.3762... Generator Loss: 0.6589
Epoch 2/2... Discriminator Loss: 1.3762... Generator Loss: 0.6353
Epoch 2/2... Discriminator Loss: 1.3633... Generator Loss: 0.6462
Epoch 2/2... Discriminator Loss: 1.3641... Generator Loss: 0.6417
Epoch 2/2... Discriminator Loss: 1.3663... Generator Loss: 0.6440
Epoch 2/2... Discriminator Loss: 1.3636... Generator Loss: 0.6492
Epoch 2/2... Discriminator Loss: 1.3743... Generator Loss: 0.6481
Epoch 2/2... Discriminator Loss: 1.3788... Generator Loss: 0.6453
Epoch 2/2... Discriminator Loss: 1.3661... Generator Loss: 0.6419
Epoch 2/2... Discriminator Loss: 1.3637... Generator Loss: 0.6349
Epoch 2/2... Discriminator Loss: 1.3702... Generator Loss: 0.6341
Epoch 2/2... Discriminator Loss: 1.3751... Generator Loss: 0.6353
Epoch 2/2... Discriminator Loss: 1.3656... Generator Loss: 0.6342
Epoch 2/2... Discriminator Loss: 1.3763... Generator Loss: 0.6428
Epoch 2/2... Discriminator Loss: 1.3745... Generator Loss: 0.6583
Epoch 2/2... Discriminator Loss: 1.3763... Generator Loss: 0.6527
Epoch 2/2... Discriminator Loss: 1.3706... Generator Loss: 0.6438
Epoch 2/2... Discriminator Loss: 1.3725... Generator Loss: 0.6549
Epoch 2/2... Discriminator Loss: 1.3699... Generator Loss: 0.6446
Epoch 2/2... Discriminator Loss: 1.3614... Generator Loss: 0.6398
Epoch 2/2... Discriminator Loss: 1.3678... Generator Loss: 0.6504
Epoch 2/2... Discriminator Loss: 1.3698... Generator Loss: 0.6332
Epoch 2/2... Discriminator Loss: 1.3590... Generator Loss: 0.6525
Epoch 2/2... Discriminator Loss: 1.3663... Generator Loss: 0.6541
Epoch 2/2... Discriminator Loss: 1.3729... Generator Loss: 0.6450
Epoch 2/2... Discriminator Loss: 1.3708... Generator Loss: 0.6374
Epoch 2/2... Discriminator Loss: 1.3716... Generator Loss: 0.6442
Epoch 2/2... Discriminator Loss: 1.3708... Generator Loss: 0.6375
Epoch 2/2... Discriminator Loss: 1.3662... Generator Loss: 0.6355
Epoch 2/2... Discriminator Loss: 1.3767... Generator Loss: 0.6490
Epoch 2/2... Discriminator Loss: 1.3703... Generator Loss: 0.6405
Epoch 2/2... Discriminator Loss: 1.3668... Generator Loss: 0.6478
Epoch 2/2... Discriminator Loss: 1.3678... Generator Loss: 0.6485
Epoch 2/2... Discriminator Loss: 1.3725... Generator Loss: 0.6421
Epoch 2/2... Discriminator Loss: 1.3658... Generator Loss: 0.6417
Epoch 2/2... Discriminator Loss: 1.3748... Generator Loss: 0.6455
Epoch 2/2... Discriminator Loss: 1.3735... Generator Loss: 0.6581
Epoch 2/2... Discriminator Loss: 1.3681... Generator Loss: 0.6487
Epoch 2/2... Discriminator Loss: 1.3700... Generator Loss: 0.6508
Epoch 2/2... Discriminator Loss: 1.3754... Generator Loss: 0.6560
Epoch 2/2... Discriminator Loss: 1.3607... Generator Loss: 0.6494
Epoch 2/2... Discriminator Loss: 1.3698... Generator Loss: 0.6435
Epoch 2/2... Discriminator Loss: 1.3651... Generator Loss: 0.6627
Epoch 2/2... Discriminator Loss: 1.3675... Generator Loss: 0.6341
Epoch 2/2... Discriminator Loss: 1.3724... Generator Loss: 0.6382
Epoch 2/2... Discriminator Loss: 1.3722... Generator Loss: 0.6315
Epoch 2/2... Discriminator Loss: 1.3736... Generator Loss: 0.6504
Epoch 2/2... Discriminator Loss: 1.3745... Generator Loss: 0.6413
Epoch 2/2... Discriminator Loss: 1.3626... Generator Loss: 0.6411
Epoch 2/2... Discriminator Loss: 1.3753... Generator Loss: 0.6547
Epoch 2/2... Discriminator Loss: 1.3729... Generator Loss: 0.6462
Epoch 2/2... Discriminator Loss: 1.3773... Generator Loss: 0.6489
Epoch 2/2... Discriminator Loss: 1.3714... Generator Loss: 0.6576
Epoch 2/2... Discriminator Loss: 1.3663... Generator Loss: 0.6478
Epoch 2/2... Discriminator Loss: 1.3657... Generator Loss: 0.6370
Epoch 2/2... Discriminator Loss: 1.3718... Generator Loss: 0.6455
Epoch 2/2... Discriminator Loss: 1.3644... Generator Loss: 0.6400
Epoch 2/2... Discriminator Loss: 1.3733... Generator Loss: 0.6415
Epoch 2/2... Discriminator Loss: 1.3755... Generator Loss: 0.6708
Epoch 2/2... Discriminator Loss: 1.3756... Generator Loss: 0.6479
Epoch 2/2... Discriminator Loss: 1.3682... Generator Loss: 0.6512
Epoch 2/2... Discriminator Loss: 1.3710... Generator Loss: 0.6386
Epoch 2/2... Discriminator Loss: 1.3677... Generator Loss: 0.6418
Epoch 2/2... Discriminator Loss: 1.3681... Generator Loss: 0.6372
Epoch 2/2... Discriminator Loss: 1.3639... Generator Loss: 0.6331
Epoch 2/2... Discriminator Loss: 1.3695... Generator Loss: 0.6487
Epoch 2/2... Discriminator Loss: 1.3740... Generator Loss: 0.6278
Epoch 2/2... Discriminator Loss: 1.3756... Generator Loss: 0.6293
Epoch 2/2... Discriminator Loss: 1.3709... Generator Loss: 0.6524
Epoch 2/2... Discriminator Loss: 1.3734... Generator Loss: 0.6377
Epoch 2/2... Discriminator Loss: 1.3484... Generator Loss: 0.6322
Epoch 2/2... Discriminator Loss: 1.3737... Generator Loss: 0.6484
Epoch 2/2... Discriminator Loss: 1.3656... Generator Loss: 0.6558
Epoch 2/2... Discriminator Loss: 1.3630... Generator Loss: 0.6371
Epoch 2/2... Discriminator Loss: 1.3750... Generator Loss: 0.6720
Epoch 2/2... Discriminator Loss: 1.3707... Generator Loss: 0.6583
Epoch 2/2... Discriminator Loss: 1.3643... Generator Loss: 0.6419
Epoch 2/2... Discriminator Loss: 1.3731... Generator Loss: 0.6417
Epoch 2/2... Discriminator Loss: 1.3698... Generator Loss: 0.6349
Epoch 2/2... Discriminator Loss: 1.3662... Generator Loss: 0.6440
Epoch 2/2... Discriminator Loss: 1.3761... Generator Loss: 0.6534
Epoch 2/2... Discriminator Loss: 1.3669... Generator Loss: 0.6383
Epoch 2/2... Discriminator Loss: 1.3618... Generator Loss: 0.6508
Epoch 2/2... Discriminator Loss: 1.3665... Generator Loss: 0.6432
Epoch 2/2... Discriminator Loss: 1.3588... Generator Loss: 0.6231
Epoch 2/2... Discriminator Loss: 1.3784... Generator Loss: 0.6518
Epoch 2/2... Discriminator Loss: 1.3705... Generator Loss: 0.6560
Epoch 2/2... Discriminator Loss: 1.3702... Generator Loss: 0.6481
Epoch 2/2... Discriminator Loss: 1.3630... Generator Loss: 0.6478
Epoch 2/2... Discriminator Loss: 1.3674... Generator Loss: 0.6236
Epoch 2/2... Discriminator Loss: 1.3535... Generator Loss: 0.6456
Epoch 2/2... Discriminator Loss: 1.3628... Generator Loss: 0.6431
Epoch 2/2... Discriminator Loss: 1.3685... Generator Loss: 0.6629
Epoch 2/2... Discriminator Loss: 1.3711... Generator Loss: 0.6579
Epoch 2/2... Discriminator Loss: 1.3718... Generator Loss: 0.6495
Epoch 2/2... Discriminator Loss: 1.3706... Generator Loss: 0.6600
Epoch 2/2... Discriminator Loss: 1.3664... Generator Loss: 0.6360
Epoch 2/2... Discriminator Loss: 1.3643... Generator Loss: 0.6288
Epoch 2/2... Discriminator Loss: 1.3815... Generator Loss: 0.6177
Epoch 2/2... Discriminator Loss: 1.3675... Generator Loss: 0.6410
Epoch 2/2... Discriminator Loss: 1.3703... Generator Loss: 0.6241
Epoch 2/2... Discriminator Loss: 1.3629... Generator Loss: 0.6269
Epoch 2/2... Discriminator Loss: 1.3767... Generator Loss: 0.6800
Epoch 2/2... Discriminator Loss: 1.3689... Generator Loss: 0.6411
Epoch 2/2... Discriminator Loss: 1.3707... Generator Loss: 0.6114
Epoch 2/2... Discriminator Loss: 1.3623... Generator Loss: 0.6194
Epoch 2/2... Discriminator Loss: 1.3718... Generator Loss: 0.6509
Epoch 2/2... Discriminator Loss: 1.3699... Generator Loss: 0.6369
Epoch 2/2... Discriminator Loss: 1.3869... Generator Loss: 0.6133
Epoch 2/2... Discriminator Loss: 1.3802... Generator Loss: 0.6005
Epoch 2/2... Discriminator Loss: 1.3705... Generator Loss: 0.6173
Epoch 2/2... Discriminator Loss: 1.3618... Generator Loss: 0.6375
Epoch 2/2... Discriminator Loss: 1.3657... Generator Loss: 0.6411
Epoch 2/2... Discriminator Loss: 1.3594... Generator Loss: 0.6289
Epoch 2/2... Discriminator Loss: 1.3555... Generator Loss: 0.6222
Epoch 2/2... Discriminator Loss: 1.3761... Generator Loss: 0.6260
Epoch 2/2... Discriminator Loss: 1.3761... Generator Loss: 0.6338
Epoch 2/2... Discriminator Loss: 1.3571... Generator Loss: 0.6171
Epoch 2/2... Discriminator Loss: 1.3655... Generator Loss: 0.6345
Epoch 2/2... Discriminator Loss: 1.3588... Generator Loss: 0.6237
Epoch 2/2... Discriminator Loss: 1.3754... Generator Loss: 0.6368
Epoch 2/2... Discriminator Loss: 1.3697... Generator Loss: 0.6268
Epoch 2/2... Discriminator Loss: 1.3753... Generator Loss: 0.6328
Epoch 2/2... Discriminator Loss: 1.3634... Generator Loss: 0.6059
Epoch 2/2... Discriminator Loss: 1.3610... Generator Loss: 0.6414
Epoch 2/2... Discriminator Loss: 1.3764... Generator Loss: 0.6363
Epoch 2/2... Discriminator Loss: 1.3739... Generator Loss: 0.6550
Epoch 2/2... Discriminator Loss: 1.4779... Generator Loss: 0.5281
Epoch 2/2... Discriminator Loss: 1.3640... Generator Loss: 0.6772
Epoch 2/2... Discriminator Loss: 1.3828... Generator Loss: 0.6678
Epoch 2/2... Discriminator Loss: 1.3688... Generator Loss: 0.6487
Epoch 2/2... Discriminator Loss: 1.3626... Generator Loss: 0.6237
Epoch 2/2... Discriminator Loss: 1.3686... Generator Loss: 0.6513
Epoch 2/2... Discriminator Loss: 1.3734... Generator Loss: 0.6772
Epoch 2/2... Discriminator Loss: 1.3779... Generator Loss: 0.6080
Epoch 2/2... Discriminator Loss: 1.3721... Generator Loss: 0.6677
Epoch 2/2... Discriminator Loss: 1.3594... Generator Loss: 0.6263
Epoch 2/2... Discriminator Loss: 1.3674... Generator Loss: 0.6445
Epoch 2/2... Discriminator Loss: 1.3586... Generator Loss: 0.6255
Epoch 2/2... Discriminator Loss: 1.3727... Generator Loss: 0.6691
Epoch 2/2... Discriminator Loss: 1.3706... Generator Loss: 0.6323
Epoch 2/2... Discriminator Loss: 1.3735... Generator Loss: 0.6201
Epoch 2/2... Discriminator Loss: 1.3696... Generator Loss: 0.6364
Epoch 2/2... Discriminator Loss: 1.3639... Generator Loss: 0.6297
Epoch 2/2... Discriminator Loss: 1.3716... Generator Loss: 0.6382
Epoch 2/2... Discriminator Loss: 1.3580... Generator Loss: 0.6443
Epoch 2/2... Discriminator Loss: 1.3583... Generator Loss: 0.6405
Epoch 2/2... Discriminator Loss: 1.3576... Generator Loss: 0.6413
Epoch 2/2... Discriminator Loss: 1.3623... Generator Loss: 0.6479
Epoch 2/2... Discriminator Loss: 1.3588... Generator Loss: 0.6331
Epoch 2/2... Discriminator Loss: 1.3638... Generator Loss: 0.6457
Epoch 2/2... Discriminator Loss: 1.3602... Generator Loss: 0.6548
Epoch 2/2... Discriminator Loss: 1.3722... Generator Loss: 0.6477
Epoch 2/2... Discriminator Loss: 1.3658... Generator Loss: 0.6508
Epoch 2/2... Discriminator Loss: 1.3772... Generator Loss: 0.5987
Epoch 2/2... Discriminator Loss: 1.3753... Generator Loss: 0.6149
Epoch 2/2... Discriminator Loss: 1.3645... Generator Loss: 0.6538
Epoch 2/2... Discriminator Loss: 1.3717... Generator Loss: 0.6458
Epoch 2/2... Discriminator Loss: 1.3676... Generator Loss: 0.6605
Epoch 2/2... Discriminator Loss: 1.3606... Generator Loss: 0.6478
Epoch 2/2... Discriminator Loss: 1.3627... Generator Loss: 0.6579
Epoch 2/2... Discriminator Loss: 1.3790... Generator Loss: 0.6425
Epoch 2/2... Discriminator Loss: 1.3636... Generator Loss: 0.6364
Epoch 2/2... Discriminator Loss: 1.3595... Generator Loss: 0.6514
Epoch 2/2... Discriminator Loss: 1.3795... Generator Loss: 0.6545
Epoch 2/2... Discriminator Loss: 1.3800... Generator Loss: 0.6796
Epoch 2/2... Discriminator Loss: 1.3734... Generator Loss: 0.6381

CelebA

Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.

In [21]:
batch_size = 32
z_dim = 32
learning_rate = 0.00005
beta1 = 0.5


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1

celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
          celeba_dataset.shape, celeba_dataset.image_mode)
Epoch 1/1... Discriminator Loss: 1.4449... Generator Loss: 0.4687
Epoch 1/1... Discriminator Loss: 1.4494... Generator Loss: 0.4747
Epoch 1/1... Discriminator Loss: 1.3430... Generator Loss: 0.5556
Epoch 1/1... Discriminator Loss: 1.2682... Generator Loss: 0.6085
Epoch 1/1... Discriminator Loss: 1.3177... Generator Loss: 0.5647
Epoch 1/1... Discriminator Loss: 1.2241... Generator Loss: 0.6408
Epoch 1/1... Discriminator Loss: 1.2123... Generator Loss: 0.6379
Epoch 1/1... Discriminator Loss: 1.2345... Generator Loss: 0.6082
Epoch 1/1... Discriminator Loss: 1.1991... Generator Loss: 0.6381
Epoch 1/1... Discriminator Loss: 1.1629... Generator Loss: 0.6620
Epoch 1/1... Discriminator Loss: 1.1673... Generator Loss: 0.6438
Epoch 1/1... Discriminator Loss: 1.1806... Generator Loss: 0.6271
Epoch 1/1... Discriminator Loss: 1.1686... Generator Loss: 0.6435
Epoch 1/1... Discriminator Loss: 1.1499... Generator Loss: 0.6512
Epoch 1/1... Discriminator Loss: 1.1821... Generator Loss: 0.6302
Epoch 1/1... Discriminator Loss: 1.1604... Generator Loss: 0.6494
Epoch 1/1... Discriminator Loss: 1.1613... Generator Loss: 0.6444
Epoch 1/1... Discriminator Loss: 1.2374... Generator Loss: 0.5937
Epoch 1/1... Discriminator Loss: 1.2305... Generator Loss: 0.6151
Epoch 1/1... Discriminator Loss: 1.2553... Generator Loss: 0.5984
Epoch 1/1... Discriminator Loss: 1.2686... Generator Loss: 0.6011
Epoch 1/1... Discriminator Loss: 1.2770... Generator Loss: 0.6045
Epoch 1/1... Discriminator Loss: 1.2875... Generator Loss: 0.6081
Epoch 1/1... Discriminator Loss: 1.2971... Generator Loss: 0.6047
Epoch 1/1... Discriminator Loss: 1.3104... Generator Loss: 0.6036
Epoch 1/1... Discriminator Loss: 1.3078... Generator Loss: 0.6010
Epoch 1/1... Discriminator Loss: 1.3075... Generator Loss: 0.5971
Epoch 1/1... Discriminator Loss: 1.3091... Generator Loss: 0.5988
Epoch 1/1... Discriminator Loss: 1.3145... Generator Loss: 0.6026
Epoch 1/1... Discriminator Loss: 1.3221... Generator Loss: 0.6043
Epoch 1/1... Discriminator Loss: 1.3306... Generator Loss: 0.5986
Epoch 1/1... Discriminator Loss: 1.3381... Generator Loss: 0.5873
Epoch 1/1... Discriminator Loss: 1.3577... Generator Loss: 0.5823
Epoch 1/1... Discriminator Loss: 1.3398... Generator Loss: 0.5920
Epoch 1/1... Discriminator Loss: 1.3776... Generator Loss: 0.5726
Epoch 1/1... Discriminator Loss: 1.3883... Generator Loss: 0.5640
Epoch 1/1... Discriminator Loss: 1.3971... Generator Loss: 0.5598
Epoch 1/1... Discriminator Loss: 1.3694... Generator Loss: 0.5829
Epoch 1/1... Discriminator Loss: 1.3630... Generator Loss: 0.5863
Epoch 1/1... Discriminator Loss: 1.3562... Generator Loss: 0.5892
Epoch 1/1... Discriminator Loss: 1.3524... Generator Loss: 0.5951
Epoch 1/1... Discriminator Loss: 1.3622... Generator Loss: 0.5912
Epoch 1/1... Discriminator Loss: 1.3519... Generator Loss: 0.6019
Epoch 1/1... Discriminator Loss: 1.3600... Generator Loss: 0.5941
Epoch 1/1... Discriminator Loss: 1.3535... Generator Loss: 0.6014
Epoch 1/1... Discriminator Loss: 1.3435... Generator Loss: 0.6020
Epoch 1/1... Discriminator Loss: 1.3516... Generator Loss: 0.5846
Epoch 1/1... Discriminator Loss: 1.3356... Generator Loss: 0.5928
Epoch 1/1... Discriminator Loss: 1.3045... Generator Loss: 0.6067
Epoch 1/1... Discriminator Loss: 1.3179... Generator Loss: 0.5920
Epoch 1/1... Discriminator Loss: 1.3501... Generator Loss: 0.5520
Epoch 1/1... Discriminator Loss: 1.3196... Generator Loss: 0.5685
Epoch 1/1... Discriminator Loss: 1.3354... Generator Loss: 0.5516
Epoch 1/1... Discriminator Loss: 1.3244... Generator Loss: 0.5676
Epoch 1/1... Discriminator Loss: 1.2953... Generator Loss: 0.5967
Epoch 1/1... Discriminator Loss: 1.3358... Generator Loss: 0.5662
Epoch 1/1... Discriminator Loss: 1.3098... Generator Loss: 0.5938
Epoch 1/1... Discriminator Loss: 1.3074... Generator Loss: 0.5914
Epoch 1/1... Discriminator Loss: 1.2928... Generator Loss: 0.6004
Epoch 1/1... Discriminator Loss: 1.3004... Generator Loss: 0.6006
Epoch 1/1... Discriminator Loss: 1.2994... Generator Loss: 0.5992
Epoch 1/1... Discriminator Loss: 1.3203... Generator Loss: 0.5803
Epoch 1/1... Discriminator Loss: 1.2834... Generator Loss: 0.5944
Epoch 1/1... Discriminator Loss: 1.2939... Generator Loss: 0.6058
Epoch 1/1... Discriminator Loss: 1.3009... Generator Loss: 0.5941
Epoch 1/1... Discriminator Loss: 1.3235... Generator Loss: 0.5769
Epoch 1/1... Discriminator Loss: 1.3002... Generator Loss: 0.5944
Epoch 1/1... Discriminator Loss: 1.2940... Generator Loss: 0.6060
Epoch 1/1... Discriminator Loss: 1.3216... Generator Loss: 0.6093
Epoch 1/1... Discriminator Loss: 1.3116... Generator Loss: 0.6089
Epoch 1/1... Discriminator Loss: 1.2986... Generator Loss: 0.6031
Epoch 1/1... Discriminator Loss: 1.3208... Generator Loss: 0.5779
Epoch 1/1... Discriminator Loss: 1.3256... Generator Loss: 0.5760
Epoch 1/1... Discriminator Loss: 1.2899... Generator Loss: 0.5951
Epoch 1/1... Discriminator Loss: 1.2811... Generator Loss: 0.5955
Epoch 1/1... Discriminator Loss: 1.2486... Generator Loss: 0.6331
Epoch 1/1... Discriminator Loss: 1.2507... Generator Loss: 0.6187
Epoch 1/1... Discriminator Loss: 1.3093... Generator Loss: 0.5716
Epoch 1/1... Discriminator Loss: 1.2311... Generator Loss: 0.6352
Epoch 1/1... Discriminator Loss: 1.2679... Generator Loss: 0.6026
Epoch 1/1... Discriminator Loss: 1.2484... Generator Loss: 0.6023
Epoch 1/1... Discriminator Loss: 1.2470... Generator Loss: 0.6072
Epoch 1/1... Discriminator Loss: 1.2513... Generator Loss: 0.6124
Epoch 1/1... Discriminator Loss: 1.2625... Generator Loss: 0.6212
Epoch 1/1... Discriminator Loss: 1.2607... Generator Loss: 0.6163
Epoch 1/1... Discriminator Loss: 1.2884... Generator Loss: 0.5754
Epoch 1/1... Discriminator Loss: 1.3079... Generator Loss: 0.5703
Epoch 1/1... Discriminator Loss: 1.2326... Generator Loss: 0.6146
Epoch 1/1... Discriminator Loss: 1.3066... Generator Loss: 0.5748
Epoch 1/1... Discriminator Loss: 1.2725... Generator Loss: 0.5975
Epoch 1/1... Discriminator Loss: 1.2782... Generator Loss: 0.5760
Epoch 1/1... Discriminator Loss: 1.2678... Generator Loss: 0.5861
Epoch 1/1... Discriminator Loss: 1.2525... Generator Loss: 0.6098
Epoch 1/1... Discriminator Loss: 1.3058... Generator Loss: 0.5677
Epoch 1/1... Discriminator Loss: 1.3188... Generator Loss: 0.5625
Epoch 1/1... Discriminator Loss: 1.1893... Generator Loss: 0.6421
Epoch 1/1... Discriminator Loss: 1.3377... Generator Loss: 0.5431
Epoch 1/1... Discriminator Loss: 1.3010... Generator Loss: 0.5651
Epoch 1/1... Discriminator Loss: 1.2483... Generator Loss: 0.6195
Epoch 1/1... Discriminator Loss: 1.1953... Generator Loss: 0.6531
Epoch 1/1... Discriminator Loss: 1.2867... Generator Loss: 0.5652
Epoch 1/1... Discriminator Loss: 1.2023... Generator Loss: 0.6472
Epoch 1/1... Discriminator Loss: 1.2949... Generator Loss: 0.5315
Epoch 1/1... Discriminator Loss: 1.2062... Generator Loss: 0.6270
Epoch 1/1... Discriminator Loss: 1.3315... Generator Loss: 0.5334
Epoch 1/1... Discriminator Loss: 1.1985... Generator Loss: 0.6341
Epoch 1/1... Discriminator Loss: 1.2554... Generator Loss: 0.5940
Epoch 1/1... Discriminator Loss: 1.2668... Generator Loss: 0.5821
Epoch 1/1... Discriminator Loss: 1.1886... Generator Loss: 0.6383
Epoch 1/1... Discriminator Loss: 1.2196... Generator Loss: 0.5952
Epoch 1/1... Discriminator Loss: 1.2738... Generator Loss: 0.5644
Epoch 1/1... Discriminator Loss: 1.2878... Generator Loss: 0.5754
Epoch 1/1... Discriminator Loss: 1.3253... Generator Loss: 0.5514
Epoch 1/1... Discriminator Loss: 1.2533... Generator Loss: 0.5950
Epoch 1/1... Discriminator Loss: 1.2329... Generator Loss: 0.6446
Epoch 1/1... Discriminator Loss: 1.1732... Generator Loss: 0.6417
Epoch 1/1... Discriminator Loss: 1.2236... Generator Loss: 0.6281
Epoch 1/1... Discriminator Loss: 1.2789... Generator Loss: 0.5815
Epoch 1/1... Discriminator Loss: 1.2868... Generator Loss: 0.5874
Epoch 1/1... Discriminator Loss: 1.3517... Generator Loss: 0.5399
Epoch 1/1... Discriminator Loss: 1.2069... Generator Loss: 0.6383
Epoch 1/1... Discriminator Loss: 1.2288... Generator Loss: 0.6052
Epoch 1/1... Discriminator Loss: 1.3603... Generator Loss: 0.5347
Epoch 1/1... Discriminator Loss: 1.1760... Generator Loss: 0.6656
Epoch 1/1... Discriminator Loss: 1.2922... Generator Loss: 0.5670
Epoch 1/1... Discriminator Loss: 1.3310... Generator Loss: 0.5576
Epoch 1/1... Discriminator Loss: 1.3468... Generator Loss: 0.5524
Epoch 1/1... Discriminator Loss: 1.2546... Generator Loss: 0.6013
Epoch 1/1... Discriminator Loss: 1.3497... Generator Loss: 0.5542
Epoch 1/1... Discriminator Loss: 1.3402... Generator Loss: 0.5757
Epoch 1/1... Discriminator Loss: 1.3325... Generator Loss: 0.5530
Epoch 1/1... Discriminator Loss: 1.3183... Generator Loss: 0.5865
Epoch 1/1... Discriminator Loss: 1.3242... Generator Loss: 0.5818
Epoch 1/1... Discriminator Loss: 1.2105... Generator Loss: 0.6587
Epoch 1/1... Discriminator Loss: 1.2325... Generator Loss: 0.6058
Epoch 1/1... Discriminator Loss: 1.3356... Generator Loss: 0.5253
Epoch 1/1... Discriminator Loss: 1.3765... Generator Loss: 0.5175
Epoch 1/1... Discriminator Loss: 1.3236... Generator Loss: 0.5753
Epoch 1/1... Discriminator Loss: 1.3355... Generator Loss: 0.5650
Epoch 1/1... Discriminator Loss: 1.3046... Generator Loss: 0.5571
Epoch 1/1... Discriminator Loss: 1.3612... Generator Loss: 0.5416
Epoch 1/1... Discriminator Loss: 1.2361... Generator Loss: 0.5862
Epoch 1/1... Discriminator Loss: 1.3282... Generator Loss: 0.5442
Epoch 1/1... Discriminator Loss: 1.2362... Generator Loss: 0.6479
Epoch 1/1... Discriminator Loss: 1.2114... Generator Loss: 0.6395
Epoch 1/1... Discriminator Loss: 1.1888... Generator Loss: 0.6655
Epoch 1/1... Discriminator Loss: 1.3881... Generator Loss: 0.5011
Epoch 1/1... Discriminator Loss: 1.2768... Generator Loss: 0.5879
Epoch 1/1... Discriminator Loss: 1.2250... Generator Loss: 0.6098
Epoch 1/1... Discriminator Loss: 1.3148... Generator Loss: 0.5569
Epoch 1/1... Discriminator Loss: 1.3532... Generator Loss: 0.5322
Epoch 1/1... Discriminator Loss: 1.2176... Generator Loss: 0.6294
Epoch 1/1... Discriminator Loss: 1.2584... Generator Loss: 0.6026
Epoch 1/1... Discriminator Loss: 1.2816... Generator Loss: 0.5836
Epoch 1/1... Discriminator Loss: 1.3304... Generator Loss: 0.5683
Epoch 1/1... Discriminator Loss: 1.2480... Generator Loss: 0.6371
Epoch 1/1... Discriminator Loss: 1.2180... Generator Loss: 0.6569
Epoch 1/1... Discriminator Loss: 1.3522... Generator Loss: 0.5486
Epoch 1/1... Discriminator Loss: 1.3728... Generator Loss: 0.5350
Epoch 1/1... Discriminator Loss: 1.3065... Generator Loss: 0.5608
Epoch 1/1... Discriminator Loss: 1.2975... Generator Loss: 0.5947
Epoch 1/1... Discriminator Loss: 1.3192... Generator Loss: 0.5579
Epoch 1/1... Discriminator Loss: 1.2870... Generator Loss: 0.5930
Epoch 1/1... Discriminator Loss: 1.3650... Generator Loss: 0.5554
Epoch 1/1... Discriminator Loss: 1.2864... Generator Loss: 0.6100
Epoch 1/1... Discriminator Loss: 1.2704... Generator Loss: 0.6274
Epoch 1/1... Discriminator Loss: 1.2380... Generator Loss: 0.6252
Epoch 1/1... Discriminator Loss: 1.2763... Generator Loss: 0.5933
Epoch 1/1... Discriminator Loss: 1.3109... Generator Loss: 0.5603
Epoch 1/1... Discriminator Loss: 1.2993... Generator Loss: 0.5801
Epoch 1/1... Discriminator Loss: 1.3383... Generator Loss: 0.5719
Epoch 1/1... Discriminator Loss: 1.2589... Generator Loss: 0.6123
Epoch 1/1... Discriminator Loss: 1.3352... Generator Loss: 0.5502
Epoch 1/1... Discriminator Loss: 1.2173... Generator Loss: 0.6572
Epoch 1/1... Discriminator Loss: 1.2679... Generator Loss: 0.5891
Epoch 1/1... Discriminator Loss: 1.3574... Generator Loss: 0.5491
Epoch 1/1... Discriminator Loss: 1.2480... Generator Loss: 0.6378
Epoch 1/1... Discriminator Loss: 1.2820... Generator Loss: 0.5772
Epoch 1/1... Discriminator Loss: 1.3269... Generator Loss: 0.5727
Epoch 1/1... Discriminator Loss: 1.3242... Generator Loss: 0.5658
Epoch 1/1... Discriminator Loss: 1.3151... Generator Loss: 0.5803
Epoch 1/1... Discriminator Loss: 1.3072... Generator Loss: 0.5853
Epoch 1/1... Discriminator Loss: 1.3461... Generator Loss: 0.5779
Epoch 1/1... Discriminator Loss: 1.2982... Generator Loss: 0.6034
Epoch 1/1... Discriminator Loss: 1.2972... Generator Loss: 0.5973
Epoch 1/1... Discriminator Loss: 1.3365... Generator Loss: 0.5705
Epoch 1/1... Discriminator Loss: 1.3288... Generator Loss: 0.5607
Epoch 1/1... Discriminator Loss: 1.3471... Generator Loss: 0.5628
Epoch 1/1... Discriminator Loss: 1.3278... Generator Loss: 0.5671
Epoch 1/1... Discriminator Loss: 1.3241... Generator Loss: 0.5786
Epoch 1/1... Discriminator Loss: 1.3055... Generator Loss: 0.5865
Epoch 1/1... Discriminator Loss: 1.2502... Generator Loss: 0.6231
Epoch 1/1... Discriminator Loss: 1.2579... Generator Loss: 0.6097
Epoch 1/1... Discriminator Loss: 1.3467... Generator Loss: 0.5550
Epoch 1/1... Discriminator Loss: 1.3084... Generator Loss: 0.5792
Epoch 1/1... Discriminator Loss: 1.3834... Generator Loss: 0.5322
Epoch 1/1... Discriminator Loss: 1.3220... Generator Loss: 0.5776
Epoch 1/1... Discriminator Loss: 1.4043... Generator Loss: 0.5201
Epoch 1/1... Discriminator Loss: 1.3277... Generator Loss: 0.5753
Epoch 1/1... Discriminator Loss: 1.2877... Generator Loss: 0.6025
Epoch 1/1... Discriminator Loss: 1.3489... Generator Loss: 0.5572
Epoch 1/1... Discriminator Loss: 1.2957... Generator Loss: 0.6020
Epoch 1/1... Discriminator Loss: 1.2892... Generator Loss: 0.6099
Epoch 1/1... Discriminator Loss: 1.3147... Generator Loss: 0.5800
Epoch 1/1... Discriminator Loss: 1.3102... Generator Loss: 0.5877
Epoch 1/1... Discriminator Loss: 1.3165... Generator Loss: 0.6041
Epoch 1/1... Discriminator Loss: 1.2964... Generator Loss: 0.6064
Epoch 1/1... Discriminator Loss: 1.2838... Generator Loss: 0.5996
Epoch 1/1... Discriminator Loss: 1.3203... Generator Loss: 0.5647
Epoch 1/1... Discriminator Loss: 1.3012... Generator Loss: 0.5757
Epoch 1/1... Discriminator Loss: 1.3788... Generator Loss: 0.5425
Epoch 1/1... Discriminator Loss: 1.3139... Generator Loss: 0.5612
Epoch 1/1... Discriminator Loss: 1.2759... Generator Loss: 0.6230
Epoch 1/1... Discriminator Loss: 1.3698... Generator Loss: 0.5459
Epoch 1/1... Discriminator Loss: 1.3339... Generator Loss: 0.5962
Epoch 1/1... Discriminator Loss: 1.2832... Generator Loss: 0.5937
Epoch 1/1... Discriminator Loss: 1.3433... Generator Loss: 0.5457
Epoch 1/1... Discriminator Loss: 1.3589... Generator Loss: 0.5491
Epoch 1/1... Discriminator Loss: 1.3289... Generator Loss: 0.5838
Epoch 1/1... Discriminator Loss: 1.3637... Generator Loss: 0.5690
Epoch 1/1... Discriminator Loss: 1.3212... Generator Loss: 0.6038
Epoch 1/1... Discriminator Loss: 1.3357... Generator Loss: 0.6021
Epoch 1/1... Discriminator Loss: 1.3584... Generator Loss: 0.5792
Epoch 1/1... Discriminator Loss: 1.3699... Generator Loss: 0.5763
Epoch 1/1... Discriminator Loss: 1.3422... Generator Loss: 0.5908
Epoch 1/1... Discriminator Loss: 1.3611... Generator Loss: 0.5823
Epoch 1/1... Discriminator Loss: 1.3735... Generator Loss: 0.5797
Epoch 1/1... Discriminator Loss: 1.3651... Generator Loss: 0.5865
Epoch 1/1... Discriminator Loss: 1.3602... Generator Loss: 0.5856
Epoch 1/1... Discriminator Loss: 1.3678... Generator Loss: 0.5918
Epoch 1/1... Discriminator Loss: 1.3533... Generator Loss: 0.5973
Epoch 1/1... Discriminator Loss: 1.3521... Generator Loss: 0.5982
Epoch 1/1... Discriminator Loss: 1.3715... Generator Loss: 0.5980
Epoch 1/1... Discriminator Loss: 1.3642... Generator Loss: 0.6045
Epoch 1/1... Discriminator Loss: 1.3744... Generator Loss: 0.6032
Epoch 1/1... Discriminator Loss: 1.3462... Generator Loss: 0.6101
Epoch 1/1... Discriminator Loss: 1.3752... Generator Loss: 0.5837
Epoch 1/1... Discriminator Loss: 1.3784... Generator Loss: 0.5820
Epoch 1/1... Discriminator Loss: 1.3397... Generator Loss: 0.6226
Epoch 1/1... Discriminator Loss: 1.3798... Generator Loss: 0.5924
Epoch 1/1... Discriminator Loss: 1.3723... Generator Loss: 0.6008
Epoch 1/1... Discriminator Loss: 1.3652... Generator Loss: 0.6036
Epoch 1/1... Discriminator Loss: 1.3780... Generator Loss: 0.5901
Epoch 1/1... Discriminator Loss: 1.3766... Generator Loss: 0.5930
Epoch 1/1... Discriminator Loss: 1.3556... Generator Loss: 0.6172
Epoch 1/1... Discriminator Loss: 1.3629... Generator Loss: 0.6166
Epoch 1/1... Discriminator Loss: 1.3695... Generator Loss: 0.6120
Epoch 1/1... Discriminator Loss: 1.3856... Generator Loss: 0.6049
Epoch 1/1... Discriminator Loss: 1.3532... Generator Loss: 0.6231
Epoch 1/1... Discriminator Loss: 1.3919... Generator Loss: 0.5996
Epoch 1/1... Discriminator Loss: 1.3757... Generator Loss: 0.6212
Epoch 1/1... Discriminator Loss: 1.3856... Generator Loss: 0.6001
Epoch 1/1... Discriminator Loss: 1.3808... Generator Loss: 0.6129
Epoch 1/1... Discriminator Loss: 1.3809... Generator Loss: 0.5869
Epoch 1/1... Discriminator Loss: 1.3623... Generator Loss: 0.6235
Epoch 1/1... Discriminator Loss: 1.3747... Generator Loss: 0.6093
Epoch 1/1... Discriminator Loss: 1.3962... Generator Loss: 0.5895
Epoch 1/1... Discriminator Loss: 1.3496... Generator Loss: 0.6255
Epoch 1/1... Discriminator Loss: 1.3972... Generator Loss: 0.5900
Epoch 1/1... Discriminator Loss: 1.3625... Generator Loss: 0.6226
Epoch 1/1... Discriminator Loss: 1.3769... Generator Loss: 0.6052
Epoch 1/1... Discriminator Loss: 1.3530... Generator Loss: 0.6155
Epoch 1/1... Discriminator Loss: 1.3792... Generator Loss: 0.5853
Epoch 1/1... Discriminator Loss: 1.3363... Generator Loss: 0.6218
Epoch 1/1... Discriminator Loss: 1.3557... Generator Loss: 0.5992
Epoch 1/1... Discriminator Loss: 1.3576... Generator Loss: 0.5991
Epoch 1/1... Discriminator Loss: 1.3782... Generator Loss: 0.5803
Epoch 1/1... Discriminator Loss: 1.3351... Generator Loss: 0.6176
Epoch 1/1... Discriminator Loss: 1.3509... Generator Loss: 0.5844
Epoch 1/1... Discriminator Loss: 1.3625... Generator Loss: 0.5671
Epoch 1/1... Discriminator Loss: 1.3418... Generator Loss: 0.6042
Epoch 1/1... Discriminator Loss: 1.3697... Generator Loss: 0.5755
Epoch 1/1... Discriminator Loss: 1.3711... Generator Loss: 0.5743
Epoch 1/1... Discriminator Loss: 1.3733... Generator Loss: 0.5696
Epoch 1/1... Discriminator Loss: 1.3539... Generator Loss: 0.5902
Epoch 1/1... Discriminator Loss: 1.3667... Generator Loss: 0.5769
Epoch 1/1... Discriminator Loss: 1.3814... Generator Loss: 0.5674
Epoch 1/1... Discriminator Loss: 1.3560... Generator Loss: 0.5875
Epoch 1/1... Discriminator Loss: 1.3495... Generator Loss: 0.5966
Epoch 1/1... Discriminator Loss: 1.3301... Generator Loss: 0.6005
Epoch 1/1... Discriminator Loss: 1.3571... Generator Loss: 0.5928
Epoch 1/1... Discriminator Loss: 1.3743... Generator Loss: 0.5668
Epoch 1/1... Discriminator Loss: 1.3652... Generator Loss: 0.5828
Epoch 1/1... Discriminator Loss: 1.3453... Generator Loss: 0.5963
Epoch 1/1... Discriminator Loss: 1.3162... Generator Loss: 0.6175
Epoch 1/1... Discriminator Loss: 1.3413... Generator Loss: 0.6015
Epoch 1/1... Discriminator Loss: 1.3581... Generator Loss: 0.6134
Epoch 1/1... Discriminator Loss: 1.3495... Generator Loss: 0.6066
Epoch 1/1... Discriminator Loss: 1.3857... Generator Loss: 0.5755
Epoch 1/1... Discriminator Loss: 1.3501... Generator Loss: 0.5768
Epoch 1/1... Discriminator Loss: 1.3072... Generator Loss: 0.6199
Epoch 1/1... Discriminator Loss: 1.3445... Generator Loss: 0.6224
Epoch 1/1... Discriminator Loss: 1.3688... Generator Loss: 0.5775
Epoch 1/1... Discriminator Loss: 1.3264... Generator Loss: 0.6209
Epoch 1/1... Discriminator Loss: 1.3729... Generator Loss: 0.5715
Epoch 1/1... Discriminator Loss: 1.3042... Generator Loss: 0.6458
Epoch 1/1... Discriminator Loss: 1.3786... Generator Loss: 0.5759
Epoch 1/1... Discriminator Loss: 1.3328... Generator Loss: 0.6180
Epoch 1/1... Discriminator Loss: 1.3262... Generator Loss: 0.6173
Epoch 1/1... Discriminator Loss: 1.3753... Generator Loss: 0.5577
Epoch 1/1... Discriminator Loss: 1.3197... Generator Loss: 0.6208
Epoch 1/1... Discriminator Loss: 1.3636... Generator Loss: 0.5913
Epoch 1/1... Discriminator Loss: 1.3572... Generator Loss: 0.5902
Epoch 1/1... Discriminator Loss: 1.3150... Generator Loss: 0.6082
Epoch 1/1... Discriminator Loss: 1.3621... Generator Loss: 0.5901
Epoch 1/1... Discriminator Loss: 1.3709... Generator Loss: 0.5841
Epoch 1/1... Discriminator Loss: 1.3533... Generator Loss: 0.5938
Epoch 1/1... Discriminator Loss: 1.3398... Generator Loss: 0.6302
Epoch 1/1... Discriminator Loss: 1.3432... Generator Loss: 0.5901
Epoch 1/1... Discriminator Loss: 1.3622... Generator Loss: 0.5619
Epoch 1/1... Discriminator Loss: 1.3455... Generator Loss: 0.5759
Epoch 1/1... Discriminator Loss: 1.3576... Generator Loss: 0.6034
Epoch 1/1... Discriminator Loss: 1.3487... Generator Loss: 0.5948
Epoch 1/1... Discriminator Loss: 1.3849... Generator Loss: 0.5682
Epoch 1/1... Discriminator Loss: 1.3780... Generator Loss: 0.5801
Epoch 1/1... Discriminator Loss: 1.3770... Generator Loss: 0.5953
Epoch 1/1... Discriminator Loss: 1.3327... Generator Loss: 0.6226
Epoch 1/1... Discriminator Loss: 1.3266... Generator Loss: 0.6092
Epoch 1/1... Discriminator Loss: 1.3624... Generator Loss: 0.5691
Epoch 1/1... Discriminator Loss: 1.3305... Generator Loss: 0.6142
Epoch 1/1... Discriminator Loss: 1.3751... Generator Loss: 0.5710
Epoch 1/1... Discriminator Loss: 1.3596... Generator Loss: 0.6043
Epoch 1/1... Discriminator Loss: 1.3405... Generator Loss: 0.6111
Epoch 1/1... Discriminator Loss: 1.3330... Generator Loss: 0.6087
Epoch 1/1... Discriminator Loss: 1.3054... Generator Loss: 0.6162
Epoch 1/1... Discriminator Loss: 1.3849... Generator Loss: 0.5319
Epoch 1/1... Discriminator Loss: 1.3372... Generator Loss: 0.6025
Epoch 1/1... Discriminator Loss: 1.3361... Generator Loss: 0.6202
Epoch 1/1... Discriminator Loss: 1.3511... Generator Loss: 0.5752
Epoch 1/1... Discriminator Loss: 1.3481... Generator Loss: 0.5996
Epoch 1/1... Discriminator Loss: 1.3287... Generator Loss: 0.6262
Epoch 1/1... Discriminator Loss: 1.3365... Generator Loss: 0.6065
Epoch 1/1... Discriminator Loss: 1.3333... Generator Loss: 0.6143
Epoch 1/1... Discriminator Loss: 1.3925... Generator Loss: 0.5581
Epoch 1/1... Discriminator Loss: 1.3808... Generator Loss: 0.5816
Epoch 1/1... Discriminator Loss: 1.3171... Generator Loss: 0.6121
Epoch 1/1... Discriminator Loss: 1.3568... Generator Loss: 0.5711
Epoch 1/1... Discriminator Loss: 1.3302... Generator Loss: 0.5763
Epoch 1/1... Discriminator Loss: 1.3485... Generator Loss: 0.6089
Epoch 1/1... Discriminator Loss: 1.3565... Generator Loss: 0.5954
Epoch 1/1... Discriminator Loss: 1.3753... Generator Loss: 0.5599
Epoch 1/1... Discriminator Loss: 1.3334... Generator Loss: 0.5995
Epoch 1/1... Discriminator Loss: 1.3565... Generator Loss: 0.5754
Epoch 1/1... Discriminator Loss: 1.3580... Generator Loss: 0.6080
Epoch 1/1... Discriminator Loss: 1.3780... Generator Loss: 0.5768
Epoch 1/1... Discriminator Loss: 1.3477... Generator Loss: 0.5923
Epoch 1/1... Discriminator Loss: 1.3784... Generator Loss: 0.5879
Epoch 1/1... Discriminator Loss: 1.3015... Generator Loss: 0.6232
Epoch 1/1... Discriminator Loss: 1.3343... Generator Loss: 0.6229
Epoch 1/1... Discriminator Loss: 1.3788... Generator Loss: 0.5891
Epoch 1/1... Discriminator Loss: 1.3232... Generator Loss: 0.6206
Epoch 1/1... Discriminator Loss: 1.3116... Generator Loss: 0.6098
Epoch 1/1... Discriminator Loss: 1.3915... Generator Loss: 0.5716
Epoch 1/1... Discriminator Loss: 1.3559... Generator Loss: 0.5891
Epoch 1/1... Discriminator Loss: 1.3644... Generator Loss: 0.6000
Epoch 1/1... Discriminator Loss: 1.3543... Generator Loss: 0.5750
Epoch 1/1... Discriminator Loss: 1.3416... Generator Loss: 0.6315
Epoch 1/1... Discriminator Loss: 1.3942... Generator Loss: 0.5663
Epoch 1/1... Discriminator Loss: 1.2891... Generator Loss: 0.6230
Epoch 1/1... Discriminator Loss: 1.3224... Generator Loss: 0.6327
Epoch 1/1... Discriminator Loss: 1.4050... Generator Loss: 0.5649
Epoch 1/1... Discriminator Loss: 1.3391... Generator Loss: 0.6385
Epoch 1/1... Discriminator Loss: 1.3940... Generator Loss: 0.5336
Epoch 1/1... Discriminator Loss: 1.3602... Generator Loss: 0.5694
Epoch 1/1... Discriminator Loss: 1.3656... Generator Loss: 0.5830
Epoch 1/1... Discriminator Loss: 1.3861... Generator Loss: 0.6229
Epoch 1/1... Discriminator Loss: 1.3430... Generator Loss: 0.5977
Epoch 1/1... Discriminator Loss: 1.3449... Generator Loss: 0.6077
Epoch 1/1... Discriminator Loss: 1.3750... Generator Loss: 0.5491
Epoch 1/1... Discriminator Loss: 1.3840... Generator Loss: 0.5810
Epoch 1/1... Discriminator Loss: 1.3576... Generator Loss: 0.6419
Epoch 1/1... Discriminator Loss: 1.3104... Generator Loss: 0.6251
Epoch 1/1... Discriminator Loss: 1.3520... Generator Loss: 0.5997
Epoch 1/1... Discriminator Loss: 1.3773... Generator Loss: 0.5915
Epoch 1/1... Discriminator Loss: 1.3596... Generator Loss: 0.5719
Epoch 1/1... Discriminator Loss: 1.3758... Generator Loss: 0.5869
Epoch 1/1... Discriminator Loss: 1.3816... Generator Loss: 0.5776
Epoch 1/1... Discriminator Loss: 1.3470... Generator Loss: 0.5934
Epoch 1/1... Discriminator Loss: 1.3558... Generator Loss: 0.6067
Epoch 1/1... Discriminator Loss: 1.3624... Generator Loss: 0.5832
Epoch 1/1... Discriminator Loss: 1.3250... Generator Loss: 0.6279
Epoch 1/1... Discriminator Loss: 1.3864... Generator Loss: 0.6022
Epoch 1/1... Discriminator Loss: 1.3223... Generator Loss: 0.5994
Epoch 1/1... Discriminator Loss: 1.3661... Generator Loss: 0.5965
Epoch 1/1... Discriminator Loss: 1.3830... Generator Loss: 0.5563
Epoch 1/1... Discriminator Loss: 1.3596... Generator Loss: 0.5892
Epoch 1/1... Discriminator Loss: 1.3753... Generator Loss: 0.6379
Epoch 1/1... Discriminator Loss: 1.3536... Generator Loss: 0.5738
Epoch 1/1... Discriminator Loss: 1.3954... Generator Loss: 0.5828
Epoch 1/1... Discriminator Loss: 1.3750... Generator Loss: 0.5751
Epoch 1/1... Discriminator Loss: 1.3215... Generator Loss: 0.6146
Epoch 1/1... Discriminator Loss: 1.3605... Generator Loss: 0.5809
Epoch 1/1... Discriminator Loss: 1.3304... Generator Loss: 0.6194
Epoch 1/1... Discriminator Loss: 1.3012... Generator Loss: 0.6253
Epoch 1/1... Discriminator Loss: 1.3862... Generator Loss: 0.5987
Epoch 1/1... Discriminator Loss: 1.3861... Generator Loss: 0.5795
Epoch 1/1... Discriminator Loss: 1.3117... Generator Loss: 0.6290
Epoch 1/1... Discriminator Loss: 1.3448... Generator Loss: 0.6079
Epoch 1/1... Discriminator Loss: 1.3624... Generator Loss: 0.5881
Epoch 1/1... Discriminator Loss: 1.3648... Generator Loss: 0.5827
Epoch 1/1... Discriminator Loss: 1.3795... Generator Loss: 0.6066
Epoch 1/1... Discriminator Loss: 1.3520... Generator Loss: 0.6140
Epoch 1/1... Discriminator Loss: 1.3607... Generator Loss: 0.5731
Epoch 1/1... Discriminator Loss: 1.3730... Generator Loss: 0.5582
Epoch 1/1... Discriminator Loss: 1.3796... Generator Loss: 0.6279
Epoch 1/1... Discriminator Loss: 1.3538... Generator Loss: 0.5788
Epoch 1/1... Discriminator Loss: 1.3440... Generator Loss: 0.5928
Epoch 1/1... Discriminator Loss: 1.3790... Generator Loss: 0.5783
Epoch 1/1... Discriminator Loss: 1.3527... Generator Loss: 0.5868
Epoch 1/1... Discriminator Loss: 1.3726... Generator Loss: 0.6354
Epoch 1/1... Discriminator Loss: 1.3266... Generator Loss: 0.6041
Epoch 1/1... Discriminator Loss: 1.3574... Generator Loss: 0.5866
Epoch 1/1... Discriminator Loss: 1.3098... Generator Loss: 0.6311
Epoch 1/1... Discriminator Loss: 1.3447... Generator Loss: 0.5711
Epoch 1/1... Discriminator Loss: 1.3617... Generator Loss: 0.6013
Epoch 1/1... Discriminator Loss: 1.3265... Generator Loss: 0.6018
Epoch 1/1... Discriminator Loss: 1.3623... Generator Loss: 0.5819
Epoch 1/1... Discriminator Loss: 1.3082... Generator Loss: 0.5828
Epoch 1/1... Discriminator Loss: 1.3463... Generator Loss: 0.6120
Epoch 1/1... Discriminator Loss: 1.3802... Generator Loss: 0.6087
Epoch 1/1... Discriminator Loss: 1.3651... Generator Loss: 0.5953
Epoch 1/1... Discriminator Loss: 1.3195... Generator Loss: 0.6231
Epoch 1/1... Discriminator Loss: 1.3794... Generator Loss: 0.5995
Epoch 1/1... Discriminator Loss: 1.3726... Generator Loss: 0.6046
Epoch 1/1... Discriminator Loss: 1.3570... Generator Loss: 0.6027
Epoch 1/1... Discriminator Loss: 1.3611... Generator Loss: 0.6128
Epoch 1/1... Discriminator Loss: 1.3374... Generator Loss: 0.6153
Epoch 1/1... Discriminator Loss: 1.3636... Generator Loss: 0.5896
Epoch 1/1... Discriminator Loss: 1.3804... Generator Loss: 0.5768
Epoch 1/1... Discriminator Loss: 1.3066... Generator Loss: 0.6382
Epoch 1/1... Discriminator Loss: 1.3693... Generator Loss: 0.5863
Epoch 1/1... Discriminator Loss: 1.3078... Generator Loss: 0.5999
Epoch 1/1... Discriminator Loss: 1.3703... Generator Loss: 0.5891
Epoch 1/1... Discriminator Loss: 1.4052... Generator Loss: 0.5817
Epoch 1/1... Discriminator Loss: 1.3689... Generator Loss: 0.6009
Epoch 1/1... Discriminator Loss: 1.3716... Generator Loss: 0.5478
Epoch 1/1... Discriminator Loss: 1.3811... Generator Loss: 0.6097
Epoch 1/1... Discriminator Loss: 1.3666... Generator Loss: 0.5947
Epoch 1/1... Discriminator Loss: 1.3868... Generator Loss: 0.6006
Epoch 1/1... Discriminator Loss: 1.3519... Generator Loss: 0.6193
Epoch 1/1... Discriminator Loss: 1.3615... Generator Loss: 0.6324
Epoch 1/1... Discriminator Loss: 1.3569... Generator Loss: 0.6145
Epoch 1/1... Discriminator Loss: 1.3511... Generator Loss: 0.5976
Epoch 1/1... Discriminator Loss: 1.3638... Generator Loss: 0.6361
Epoch 1/1... Discriminator Loss: 1.3776... Generator Loss: 0.5818
Epoch 1/1... Discriminator Loss: 1.3582... Generator Loss: 0.5438
Epoch 1/1... Discriminator Loss: 1.3284... Generator Loss: 0.5935
Epoch 1/1... Discriminator Loss: 1.3619... Generator Loss: 0.5794
Epoch 1/1... Discriminator Loss: 1.3528... Generator Loss: 0.5800
Epoch 1/1... Discriminator Loss: 1.3731... Generator Loss: 0.6264
Epoch 1/1... Discriminator Loss: 1.3524... Generator Loss: 0.6188
Epoch 1/1... Discriminator Loss: 1.3336... Generator Loss: 0.6109
Epoch 1/1... Discriminator Loss: 1.3738... Generator Loss: 0.5810
Epoch 1/1... Discriminator Loss: 1.3793... Generator Loss: 0.6092
Epoch 1/1... Discriminator Loss: 1.3924... Generator Loss: 0.5852
Epoch 1/1... Discriminator Loss: 1.3751... Generator Loss: 0.5844
Epoch 1/1... Discriminator Loss: 1.3615... Generator Loss: 0.6221
Epoch 1/1... Discriminator Loss: 1.3916... Generator Loss: 0.6021
Epoch 1/1... Discriminator Loss: 1.3513... Generator Loss: 0.6231
Epoch 1/1... Discriminator Loss: 1.3606... Generator Loss: 0.6028
Epoch 1/1... Discriminator Loss: 1.3411... Generator Loss: 0.6293
Epoch 1/1... Discriminator Loss: 1.3520... Generator Loss: 0.6368
Epoch 1/1... Discriminator Loss: 1.3636... Generator Loss: 0.6154
Epoch 1/1... Discriminator Loss: 1.3528... Generator Loss: 0.6103
Epoch 1/1... Discriminator Loss: 1.3835... Generator Loss: 0.5831
Epoch 1/1... Discriminator Loss: 1.3773... Generator Loss: 0.6017
Epoch 1/1... Discriminator Loss: 1.3802... Generator Loss: 0.6079
Epoch 1/1... Discriminator Loss: 1.3801... Generator Loss: 0.6039
Epoch 1/1... Discriminator Loss: 1.3640... Generator Loss: 0.6295
Epoch 1/1... Discriminator Loss: 1.3547... Generator Loss: 0.6079
Epoch 1/1... Discriminator Loss: 1.3758... Generator Loss: 0.6296
Epoch 1/1... Discriminator Loss: 1.3694... Generator Loss: 0.6045
Epoch 1/1... Discriminator Loss: 1.3549... Generator Loss: 0.6180
Epoch 1/1... Discriminator Loss: 1.3859... Generator Loss: 0.6135
Epoch 1/1... Discriminator Loss: 1.3722... Generator Loss: 0.5839
Epoch 1/1... Discriminator Loss: 1.3902... Generator Loss: 0.6106
Epoch 1/1... Discriminator Loss: 1.3841... Generator Loss: 0.6143
Epoch 1/1... Discriminator Loss: 1.3268... Generator Loss: 0.6284
Epoch 1/1... Discriminator Loss: 1.3823... Generator Loss: 0.5837
Epoch 1/1... Discriminator Loss: 1.3323... Generator Loss: 0.6350
Epoch 1/1... Discriminator Loss: 1.3720... Generator Loss: 0.6188
Epoch 1/1... Discriminator Loss: 1.3688... Generator Loss: 0.6226
Epoch 1/1... Discriminator Loss: 1.3679... Generator Loss: 0.6296
Epoch 1/1... Discriminator Loss: 1.3726... Generator Loss: 0.5997
Epoch 1/1... Discriminator Loss: 1.3911... Generator Loss: 0.6008
Epoch 1/1... Discriminator Loss: 1.3655... Generator Loss: 0.6276
Epoch 1/1... Discriminator Loss: 1.3845... Generator Loss: 0.6138
Epoch 1/1... Discriminator Loss: 1.3812... Generator Loss: 0.5975
Epoch 1/1... Discriminator Loss: 1.3665... Generator Loss: 0.6277
Epoch 1/1... Discriminator Loss: 1.3805... Generator Loss: 0.6021
Epoch 1/1... Discriminator Loss: 1.3435... Generator Loss: 0.6221
Epoch 1/1... Discriminator Loss: 1.3718... Generator Loss: 0.6226
Epoch 1/1... Discriminator Loss: 1.3581... Generator Loss: 0.6238
Epoch 1/1... Discriminator Loss: 1.3760... Generator Loss: 0.6103
Epoch 1/1... Discriminator Loss: 1.3734... Generator Loss: 0.6375
Epoch 1/1... Discriminator Loss: 1.3954... Generator Loss: 0.6103
Epoch 1/1... Discriminator Loss: 1.3710... Generator Loss: 0.6280
Epoch 1/1... Discriminator Loss: 1.3778... Generator Loss: 0.6057
Epoch 1/1... Discriminator Loss: 1.3487... Generator Loss: 0.6229
Epoch 1/1... Discriminator Loss: 1.3562... Generator Loss: 0.6346
Epoch 1/1... Discriminator Loss: 1.3580... Generator Loss: 0.6274
Epoch 1/1... Discriminator Loss: 1.3865... Generator Loss: 0.6171
Epoch 1/1... Discriminator Loss: 1.3654... Generator Loss: 0.6072
Epoch 1/1... Discriminator Loss: 1.3939... Generator Loss: 0.5823
Epoch 1/1... Discriminator Loss: 1.3793... Generator Loss: 0.6035
Epoch 1/1... Discriminator Loss: 1.3622... Generator Loss: 0.6213
Epoch 1/1... Discriminator Loss: 1.3858... Generator Loss: 0.6184
Epoch 1/1... Discriminator Loss: 1.3693... Generator Loss: 0.6371
Epoch 1/1... Discriminator Loss: 1.3860... Generator Loss: 0.6048
Epoch 1/1... Discriminator Loss: 1.3851... Generator Loss: 0.6224
Epoch 1/1... Discriminator Loss: 1.3822... Generator Loss: 0.6204
Epoch 1/1... Discriminator Loss: 1.3833... Generator Loss: 0.6125
Epoch 1/1... Discriminator Loss: 1.3542... Generator Loss: 0.6457
Epoch 1/1... Discriminator Loss: 1.3916... Generator Loss: 0.5601
Epoch 1/1... Discriminator Loss: 1.3896... Generator Loss: 0.6305
Epoch 1/1... Discriminator Loss: 1.3895... Generator Loss: 0.6033
Epoch 1/1... Discriminator Loss: 1.3818... Generator Loss: 0.6072
Epoch 1/1... Discriminator Loss: 1.3848... Generator Loss: 0.6064
Epoch 1/1... Discriminator Loss: 1.3844... Generator Loss: 0.6254
Epoch 1/1... Discriminator Loss: 1.3778... Generator Loss: 0.6397
Epoch 1/1... Discriminator Loss: 1.3708... Generator Loss: 0.6088
Epoch 1/1... Discriminator Loss: 1.3616... Generator Loss: 0.6310
Epoch 1/1... Discriminator Loss: 1.3922... Generator Loss: 0.6277
Epoch 1/1... Discriminator Loss: 1.3741... Generator Loss: 0.6208
Epoch 1/1... Discriminator Loss: 1.3674... Generator Loss: 0.6262
Epoch 1/1... Discriminator Loss: 1.3737... Generator Loss: 0.6143
Epoch 1/1... Discriminator Loss: 1.3619... Generator Loss: 0.6209
Epoch 1/1... Discriminator Loss: 1.3894... Generator Loss: 0.6284
Epoch 1/1... Discriminator Loss: 1.3766... Generator Loss: 0.6204
Epoch 1/1... Discriminator Loss: 1.3907... Generator Loss: 0.6079
Epoch 1/1... Discriminator Loss: 1.3888... Generator Loss: 0.6392
Epoch 1/1... Discriminator Loss: 1.3712... Generator Loss: 0.6095
Epoch 1/1... Discriminator Loss: 1.3818... Generator Loss: 0.6267
Epoch 1/1... Discriminator Loss: 1.3636... Generator Loss: 0.6409
Epoch 1/1... Discriminator Loss: 1.3588... Generator Loss: 0.5952
Epoch 1/1... Discriminator Loss: 1.3719... Generator Loss: 0.6335
Epoch 1/1... Discriminator Loss: 1.3847... Generator Loss: 0.6179
Epoch 1/1... Discriminator Loss: 1.3239... Generator Loss: 0.6188
Epoch 1/1... Discriminator Loss: 1.3656... Generator Loss: 0.6263
Epoch 1/1... Discriminator Loss: 1.4007... Generator Loss: 0.5993
Epoch 1/1... Discriminator Loss: 1.3821... Generator Loss: 0.5908
Epoch 1/1... Discriminator Loss: 1.3693... Generator Loss: 0.6126
Epoch 1/1... Discriminator Loss: 1.3788... Generator Loss: 0.6132
Epoch 1/1... Discriminator Loss: 1.3811... Generator Loss: 0.6198
Epoch 1/1... Discriminator Loss: 1.3791... Generator Loss: 0.6323
Epoch 1/1... Discriminator Loss: 1.3544... Generator Loss: 0.6217
Epoch 1/1... Discriminator Loss: 1.3773... Generator Loss: 0.6323
Epoch 1/1... Discriminator Loss: 1.3687... Generator Loss: 0.6242
Epoch 1/1... Discriminator Loss: 1.3700... Generator Loss: 0.6444
Epoch 1/1... Discriminator Loss: 1.3898... Generator Loss: 0.5939
Epoch 1/1... Discriminator Loss: 1.3831... Generator Loss: 0.6119
Epoch 1/1... Discriminator Loss: 1.3778... Generator Loss: 0.6203
Epoch 1/1... Discriminator Loss: 1.3585... Generator Loss: 0.6392
Epoch 1/1... Discriminator Loss: 1.3586... Generator Loss: 0.6119
Epoch 1/1... Discriminator Loss: 1.3635... Generator Loss: 0.6224
Epoch 1/1... Discriminator Loss: 1.3788... Generator Loss: 0.6179
Epoch 1/1... Discriminator Loss: 1.3778... Generator Loss: 0.6399
Epoch 1/1... Discriminator Loss: 1.3821... Generator Loss: 0.6091
Epoch 1/1... Discriminator Loss: 1.3878... Generator Loss: 0.6363
Epoch 1/1... Discriminator Loss: 1.3832... Generator Loss: 0.6159
Epoch 1/1... Discriminator Loss: 1.3558... Generator Loss: 0.6399
Epoch 1/1... Discriminator Loss: 1.3856... Generator Loss: 0.6091
Epoch 1/1... Discriminator Loss: 1.3783... Generator Loss: 0.6277
Epoch 1/1... Discriminator Loss: 1.3702... Generator Loss: 0.6288
Epoch 1/1... Discriminator Loss: 1.3833... Generator Loss: 0.6018
Epoch 1/1... Discriminator Loss: 1.3739... Generator Loss: 0.6266
Epoch 1/1... Discriminator Loss: 1.3833... Generator Loss: 0.6195
Epoch 1/1... Discriminator Loss: 1.3823... Generator Loss: 0.6248
Epoch 1/1... Discriminator Loss: 1.3786... Generator Loss: 0.6126
Epoch 1/1... Discriminator Loss: 1.3849... Generator Loss: 0.6247
Epoch 1/1... Discriminator Loss: 1.3705... Generator Loss: 0.6052
Epoch 1/1... Discriminator Loss: 1.3930... Generator Loss: 0.6255
Epoch 1/1... Discriminator Loss: 1.3724... Generator Loss: 0.6415
Epoch 1/1... Discriminator Loss: 1.3879... Generator Loss: 0.6194
Epoch 1/1... Discriminator Loss: 1.3773... Generator Loss: 0.6413
Epoch 1/1... Discriminator Loss: 1.3835... Generator Loss: 0.6427
Epoch 1/1... Discriminator Loss: 1.3850... Generator Loss: 0.6210
Epoch 1/1... Discriminator Loss: 1.3698... Generator Loss: 0.6217
Epoch 1/1... Discriminator Loss: 1.3840... Generator Loss: 0.6271
Epoch 1/1... Discriminator Loss: 1.3883... Generator Loss: 0.6570
Epoch 1/1... Discriminator Loss: 1.3682... Generator Loss: 0.6513
Epoch 1/1... Discriminator Loss: 1.3888... Generator Loss: 0.6017
Epoch 1/1... Discriminator Loss: 1.3756... Generator Loss: 0.6427
Epoch 1/1... Discriminator Loss: 1.3795... Generator Loss: 0.6202
Epoch 1/1... Discriminator Loss: 1.3847... Generator Loss: 0.6136
Epoch 1/1... Discriminator Loss: 1.3711... Generator Loss: 0.6366
Epoch 1/1... Discriminator Loss: 1.3849... Generator Loss: 0.6470
Epoch 1/1... Discriminator Loss: 1.3928... Generator Loss: 0.6035
Epoch 1/1... Discriminator Loss: 1.3889... Generator Loss: 0.6321
Epoch 1/1... Discriminator Loss: 1.3713... Generator Loss: 0.6317
Epoch 1/1... Discriminator Loss: 1.3698... Generator Loss: 0.6420
Epoch 1/1... Discriminator Loss: 1.3741... Generator Loss: 0.6409
Epoch 1/1... Discriminator Loss: 1.3836... Generator Loss: 0.6547
Epoch 1/1... Discriminator Loss: 1.3876... Generator Loss: 0.6496
Epoch 1/1... Discriminator Loss: 1.3758... Generator Loss: 0.6193
Epoch 1/1... Discriminator Loss: 1.3679... Generator Loss: 0.6294
Epoch 1/1... Discriminator Loss: 1.3852... Generator Loss: 0.6358
Epoch 1/1... Discriminator Loss: 1.3620... Generator Loss: 0.6226
Epoch 1/1... Discriminator Loss: 1.3847... Generator Loss: 0.6303
Epoch 1/1... Discriminator Loss: 1.3692... Generator Loss: 0.6184
Epoch 1/1... Discriminator Loss: 1.3850... Generator Loss: 0.6328
Epoch 1/1... Discriminator Loss: 1.3902... Generator Loss: 0.6265
Epoch 1/1... Discriminator Loss: 1.3904... Generator Loss: 0.6196
Epoch 1/1... Discriminator Loss: 1.3776... Generator Loss: 0.6383
Epoch 1/1... Discriminator Loss: 1.3665... Generator Loss: 0.6475
Epoch 1/1... Discriminator Loss: 1.3859... Generator Loss: 0.6392
Epoch 1/1... Discriminator Loss: 1.3792... Generator Loss: 0.6477
Epoch 1/1... Discriminator Loss: 1.3800... Generator Loss: 0.6389
Epoch 1/1... Discriminator Loss: 1.3866... Generator Loss: 0.6104
Epoch 1/1... Discriminator Loss: 1.3817... Generator Loss: 0.6347
Epoch 1/1... Discriminator Loss: 1.3764... Generator Loss: 0.6361
Epoch 1/1... Discriminator Loss: 1.3844... Generator Loss: 0.6260
Epoch 1/1... Discriminator Loss: 1.3851... Generator Loss: 0.6399
Epoch 1/1... Discriminator Loss: 1.3829... Generator Loss: 0.6296
Epoch 1/1... Discriminator Loss: 1.3793... Generator Loss: 0.6448
Epoch 1/1... Discriminator Loss: 1.3687... Generator Loss: 0.6461
Epoch 1/1... Discriminator Loss: 1.3806... Generator Loss: 0.6408
Epoch 1/1... Discriminator Loss: 1.3851... Generator Loss: 0.6429
Epoch 1/1... Discriminator Loss: 1.3745... Generator Loss: 0.6325
Epoch 1/1... Discriminator Loss: 1.3771... Generator Loss: 0.6322
Epoch 1/1... Discriminator Loss: 1.3881... Generator Loss: 0.6447
Epoch 1/1... Discriminator Loss: 1.3914... Generator Loss: 0.6343
Epoch 1/1... Discriminator Loss: 1.3642... Generator Loss: 0.6347
Epoch 1/1... Discriminator Loss: 1.3752... Generator Loss: 0.6555
Epoch 1/1... Discriminator Loss: 1.3844... Generator Loss: 0.6586
Epoch 1/1... Discriminator Loss: 1.3809... Generator Loss: 0.6554
Epoch 1/1... Discriminator Loss: 1.3739... Generator Loss: 0.6420
Epoch 1/1... Discriminator Loss: 1.3834... Generator Loss: 0.6208
Epoch 1/1... Discriminator Loss: 1.3756... Generator Loss: 0.6556
Epoch 1/1... Discriminator Loss: 1.3727... Generator Loss: 0.6314
Epoch 1/1... Discriminator Loss: 1.3601... Generator Loss: 0.6441
Epoch 1/1... Discriminator Loss: 1.3922... Generator Loss: 0.6521
Epoch 1/1... Discriminator Loss: 1.3738... Generator Loss: 0.6377

Submitting This Project

When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.

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